analysis of individual health insurance data pertaining to pap

Transcription

ANALYSIS OF INDIVIDUAL HEALTH INSURANCE DATA
PERTAINING TO PAP SMEARS, COLPOSCOPIES, BIOPSIES
AND SURGERY ON THE UTERINE CERVIX
(Belgium, 2002-2006)
Marc ARBYN1,2, Cindy SIMOENS2, Valérie FABRI3,4
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European Network for Cervical Cancer Screening
Scientific Institute of Public Health, OD Public Health and Surveillance, Section Health
Services Research, Unit of Cancer Epidemiology, Brussels
Socialist mutual benefit society, Brussels
Intermutualistisch Agentschap/Agence Intermutualiste, Brussels
Health Services Research
Unit of Cancer Epidemiology
J. Wytsmanstreet 14
1050 Brussels | Belgium
www.wiv-isp.be
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Public Health and Surveillance | September 2010 | Brussels, Belgium
N° internal reference: 2010-021
N° deposit or ISSN: D/2010/2505/42
The project is financially supported by
(1) the European Commission (Directorate of SANCO, Luxembourg,
Grand-Duchy of Luxembourg), through the ECCG project
(European Cooperation on development and implementation of
Cancer screening and prevention Guidelines, IARC, Lyon, France)
and the 7th Framework Programme of DG Research of the
European Commission through the PREHDICT project (grant No.
242061, coordinated by the Vrije Universiteit Amsterdam, the
Netherlands) and the EUROCOURSE project (coordinated by the
Comprehensive
Cancer
Centre
South,
Eindhoven,
the
Netherlands);
(2) the Belgian Foundation Against Cancer (Brussels, Belgium);
(3) the Institute for the Promotion of Innovation by Science and
Technology in Flanders (IWT-Vlaanderen, refnum 060081) and
(4) FNRS (le Fonds national de la Recherche scientifique) through
TELEVIE, Brussels, Belgium (ref 7.4.628.07.F).
© Scientific Institute of Public Health, Brussels 2010
This report may not be reproduced, published or distributed without the consent of the ISP | WIV.
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Acknowledgments
We are grateful to IMA-AIM for the data files provided.
Further, we acknowledge Dr. Johan Van der Heyden and Mr. Stefaan
Demarest for providing data from the national Health Interview Surveys,
and Mr. Chris Engels and Mr. Johan Peetermans for providing NIHDI
data.
We are grateful to Prof. Philippe Beutels and Dr. Michel Boutsen for the
critical reviewing of the report.
© Scientific Institute of Public Health, Brussels 2010
This report may not be reproduced, published or distributed without the consent of the ISP | WIV.
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Analysis of individual health insurance data pertaining to
Pap smears, colposcopies, biopsies and surgery on the
uterine cervix
(Belgium, 2002-2006)
1. Table of contents
1.
TABLE OF CONTENTS..............................................................................................................7
2.
EXECUTIVE SUMMARY...........................................................................................................9
3.
RESUME ET COMMENTAIRES ............................................................................................13
4.
SAMENVATTING EN COMMENTAAR................................................................................17
5.
INTRODUCTION.......................................................................................................................21
6.
MATERIAL AND METHODS..................................................................................................23
7.
RESULTS ....................................................................................................................................26
7.1.
CYTOLOGICAL INTERPRETATION OF PAP SMEARS OF THE UTERINE CERVIX ...........................26
7.1.1. National level..................................................................................................................26
7.1.2. Regional level .................................................................................................................36
7.1.3. Provincial level...............................................................................................................41
7.2.
SCREENING COVERAGE BY SOCIAL STATUS ...........................................................................46
7.2.1. BIR status........................................................................................................................46
7.2.2. 3-year interval screening coverage by BIR status ..........................................................48
7.3.
PROFESSION OF PAP SMEAR TAKERS ......................................................................................55
7.3.1. Regional level .................................................................................................................56
7.4.
INTERVAL BETWEEN SUCCESSIVE PAP SMEARS......................................................................59
7.5.
COLPOSCOPIES & CERVICAL BIOPSIES ...................................................................................63
7.6.
HYSTERECTOMIES .................................................................................................................66
7.6.1. National level..................................................................................................................66
7.6.2. Regional level .................................................................................................................70
7.7.
CYTOLOGICAL SCREENING IN HYSTERECTOMISED WOMEN ....................................................74
7.7.1. Use of Pap smears one year after hysterectomy .............................................................74
7.7.2. Use of Pap smears in the 3-year period following hysterectomy....................................77
8.
DISCUSSION ..............................................................................................................................79
8.1.
8.2.
8.3.
QUALITY OF THE DATASET ....................................................................................................79
COMPARISON WITH RESULTS OF THE NATIONAL HEALTH INTERVIEW SURVEY (HIS) ...........79
COMPARISON WITH STATISTICS FROM THE NATIONAL INSTITUTE FOR HEALTH AND
DISABILITY INSURANCE ........................................................................................................82
8.3.1. Collection and interpretation of cervical smears ...........................................................82
8.3.2. Colposcopies................................................................................................................... 88
8.3.3. Hysterectomies................................................................................................................89
8.4.
PREVALENCE OF CYTOLOGICAL CERVICAL LESIONS ..............................................................91
8.5.
CONCLUSIONS .......................................................................................................................92
8.6.
PROPOSITIONS FOR FURTHER RESEARCH................................................................................95
9.
GLOSSARY ................................................................................................................................96
10.
ABBREVIATIONS ................................................................................................................97
11.
REFERENCES.......................................................................................................................98
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12.
12.1.
12.2.
12.3.
12.4.
12.5.
12.6.
12.7.
12.8.
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ANNEXES............................................................................................................................. 102
DEFINITION OF THE BIR (BIM-RVV) STATUS ..................................................................... 102
PAP SMEARS WITH LIMITED UTILITY AND THEIR ASSOCIATED COSTS FOR NIHDI ................ 104
CERVICAL CYTOLOGY USE BY ONE-YEAR INTERVALS, BY AGE AND REGION ........................ 106
CERVICAL CYTOLOGY USE BY THREE-YEAR INTERVALS, BY AGE AND PROVINCE ................ 108
3-YEAR PAP SMEAR USE BY AGE GROUP, PROVINCE AND BIR STATUS ................................. 117
PROFESSION OF SMEAR TAKERS, BY PROVINCE .................................................................... 123
INTERVAL BETWEEN SUCCESSIVE PAP SMEARS, BY AGE GROUP .......................................... 124
DATA FILES AND STATISTICAL SYNTAXIS FILES ................................................................... 125
2. Executive summary
Background
In 2003, the Council of Europe, recommended to offer organised cytological cervical
cancer screening to all women of the target population in all EU member states. An
optimal coverage is the main determinant of success of such a screening programme.
The current report aims to assess the cytological screening coverage and also the
consumption of medical acts for screening and follow-up or treatment of screendetected cervical lesions using a data file obtained from the Intermutualistic Agency
(Intermutualistisch Agentschap – l’Agence Intermutualiste IMA-AIM), which pools
information from all mutual sickness fundsa in Belgium. The current report is the
second of his type following a previous one targeting the period 1996-2000.
The underlying study can be used to improve future cervical cancer screening
programmes.
Material and methods
On demand of the Scientific Institute of Public Health, a data file containing more
than 14 million individual patient records was compiled by the Intermutualistic
Agency (IMA-AIM). It contained information of all medical acts related to cervical
screening, and diagnostic or therapeutic interventions on the uterine cervix (Pap smear
collection and interpretation, colposcopies, cervical biopsies and their interpretation,
surgery on the cervix) for the years 2002 to 2006.
Results
Screening coverage in Belgium, the regions and provinces
The cervical cancer screening coverage, defined as the proportion of the target
population of women between 25 and 64 years old, that had a Pap smear taken in the
last 3 years, measured in 2006, was 61%. Similar to the preceding report, the range of
variation in screening coverage at the level of the regions was small: 60% in the
Flemish Region, 62% in the Brussels-Capital Region and 63% in the Walloon Region.
Differences at provincial levels were larger and ranged from 51% (Luxembourg) to
70% (Walloon Brabant).
Overall, the screening coverage increased with 2.2% compared to 2000. The increase
was more pronounced in the Brussels-Capital Region (+4.3%) and between 2 and 3%
for the other two regions. In most provinces, the screening coverage increased
(between 0.9% and 4.3%), at the exception of two provinces where a small decrease
was noted (Limburg [-0.2%] and Luxembourg [-0.3%]).
a
The word ‘mutualité’ is quite clear in French language. In English it is close to the principle of
‘provident funds’ and ‘friendly societies’(not ‘insurance mutuals’ or US-style ‘mutual funds’). In this
publication the term is used to represent ‘mutualité’: ‘mutuality, ‘mutual sickness fund’ and ‘mutual
health fund’.
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Age groups
At the national level, the youngest age groups of the target population (25-34 years),
were the best screened with a coverage of 70%. From the age of 35 to 49, the
coverage decreased gradually from 67% to 62%. From the age of 50, the coverage
dropped more steeply to reach a level of 44% in the age group 60-64. The age profile
was similar in the three regions. However, in the Brussels-Capital Region and
Walloon Region the decline in the age group 50-64 was less pronounced than in the
Flemish Region.
Social status
Remarkable contrasts were noted between women who benefit or not from increased
reimbursement for health care (Beneficiary of Increased Reimbursement (BIR))b. In
the whole Belgian target population, the screening coverage was respectively 40%
and 64% in women with and without the BIR status. The differences between the two
social categories were consistent over all age groups and geographical areas but
varied in magnitude. At regional level, the difference varied between 21% (BrusselsCapital Region) and 27% (Flemish Region). At provincial level, the difference
ranged between 21% (Brussels) and 33% (Walloon-Brabant). The contrast changed
also by age group: in the range 22-25% for women aged 25-44 years and less for
younger and older women.
Comparison with interview surveys
The coverage computed from the individual health insurance data file was
substantially lower than the estimates derived from the national health interview
surveys. For instance at national level, for the years 2002-2004, this difference was
11.5%. This discrepancy was already observed in the previous report and is probably
due to reporting biases, which are inherent to interview surveys. Also in the
international literature, self-reported screening status systematically appears to be
overestimated compared to the true coverage.
Screening interval and target age range
The modal screening interval was 12-15 months. A time span of 36 months or more
was observed in only 3 % of women with 2 or more smears in the studied time period,
whereas in 30% it was less than 12 months. This latter proportion decreased by age.
Ten percent of all interpreted Pap smears were taken from women younger than 25
years and 8% in women older than 64 years.
Profession of Pap smear takers
The proportion of smears taken by general practitioners (GP) was limited but varied
substantially by region: in 2004-2006, 16% was taken by GPs in the Flemish Region,
whereas only 7% and 3% in the Brussels-Capital and Walloon Region, respectively.
The percentage of smears taken by a GP decreased over time, in particular in the
Flemish Region (26% in 1996, 14% in 2006).
Consumption of Pap smears
The amount of smears was theoretically sufficient to cover more than 100% of the
target population over a time span of 3 years. In 2006, the ratio of the number of Pap
b
Beneficiary of Increased Reimbursement (BIR), in Dutch: Rechthebbenden op de verhoogde
verzekeringstegemoetkoming (RVV); in French: Bénéficiaire de l’intervention majorée (BIM).
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smear interpretations over the respective mid-year target population was 1.15. This
ratio should be higher if we were able to adjust the size of the target population by
excluding women whose cervix is removed. Nevertheless, only 61% was covered
with one or more smears. In absolute figures: 3.2 million Pap smears were interpreted
in the period 2004-2006 which were taken from only 1.7 million women in the age
range 25 to 64 years. More than one million women (1.1 million) women not have a
Pap smear taken.
Costs of over-screening
The excess use of cervical cytological examinations was 88%, which means that each
screened woman received 1.88 smears over a 3-year period. The excess smear use
was high in all parts of Belgium. However, it was less high in the Flemish Region
(84%), compared to the Brussels-Capital (95%) and Walloon Region (94%).
Of course, a part of this “excess” was used for follow-up of women with a previous
cervical abnormality. Assuming that 10% of the screened women needed on average
two follow-up Pap smears, we can estimate that yearly about 380,000 Pap smears
were taken that did not contribute to screening coverage or follow-up. This
corresponds with an estimated amount of € 7.9 million per year reimbursed by the
National Institute for Health and Disability Insurance (NIHDI) for taking and reading
Pap smears with limited utility. This amount is further increased with € 4.7 million
for screening beyond the target age range.
Colposcopy use
An impressive amount of colposcopies were performed in Belgium. At the national
level, on average, one colposcopic examination was done for every 3 Pap smears. In
the Walloon Region the ratio of the number of Pap smears over the number of
colposcopies was even less than two, whereas for the Flemish Region this ratio was
eight.
The biopsy/colposcopy ratio was low (on average 5%) which can be attributed to the
very high frequency of colposcopy in women without cervical abnormalities.
It is clear that colposcopy was not used as indicated in national or international
guidelines. Colposcopic exploration is indicated in case of a first observation of HSIL
or glandular abnormality or after a second observation of ASC-US or LSIL or after a
positive HPV triage result in AS-CUS-cases and in follow-up after treated lesions.
General conclusions
The results of the current report (2002-2006) are similar to those of the previous
report (1996-2000). The cervical cancer screening coverage in Belgium, defined as
the proportion of women in the 25-64 year age range that received a Pap smear in the
last 3 years, was only 61%. Nevertheless, the amount of smears was theoretically
sufficient to cover the whole target population. This coverage was 2% higher in 2006
compared to 2000.
The coverage was substantially lower among socially vulnerable groups: 40% among
women with BIR, whereas 64% among women without BIR.
Estimation of the cervical cancer screening coverage, derived from interview surveys
should be interpreted with caution, given the inherent risk of overestimation.
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Most often smears were taken by gynaecologists; in the Walloon Region, it is almost
an exclusivity.
Colposcopy was too often used simultaneously with the Pap smear, whereas its main
clinical indication is the exploration of women with certain cytological abnormalities.
Structural reduction of the excess use and re-investment in coverage and quality
improvement can potentially result in more life-years saved, without increase in
public funding.
Measures foreseen in the European Council Recommendation on Cancer screening
should be binding and universal (in all regions). The fact that hardly any evolution in
screening coverage was observed over the last ten years, demonstrates the necessity of
a well-organised cervical cancer screening programme and clear information for the
physicians and women.
Health authorities of the Federal and Community
Governments and representatives of the scientific societies should meet as soon as
possible in order to define a rational, evidence-based and cost-effective cervical
cancer screening policy.
In the context of the actual opportunistic screening, an organized cervical cancer
screening programme should deal with the questions linked with the two major
problems identified in the current study:
1) How can the excess consumption of Pap smears among currently screened
women be reduced?
2) How can the 39% of the target population that is currently not covered be
reached and convinced to participate regularly (every three years)?
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3. Résumé et commentaires
Historique
En 2003, le Conseil européen a recommandé d’offrir un dépistage cytologique
organisé du cancer du col de l’utérus à toutes les femmes de la population-cible dans
tous les Etats-membres de l’UE. Une couverture optimale est le principal facteur de
succès d’un programme de dépistage.
Le rapport actuel a pour but d’évaluer la couverture réelle du dépistage cytologique
ainsi que l’utilisation d’actes médicaux pour le dépistage et le suivi ou traitement des
lésions précancéreuses détectés lors du dépistage en utilisant un fichier de données
provenant de l’Agence Intermutualiste (AIM), qui rassemble l’information de toutes
les mutuelles en Belgique.
Ce rapport est précédé d’un rapport similaire étudiant les années 1996-2000.
L’étude pourra être utilisée pour définir les futures stratégies de dépistage du cancer
du col de l’utérus.
Matériel et méthodes
A la demande de l’Institut Scientifique de Santé Publique, un fichier de données
individuelles de plus de 14 millions d’enregistrements individuels a été compilé par
l’Agence Intermutualiste. Ce fichier contient l’information de tous les actes médicaux
se rapportant au dépistage du cancer du col de l’utérus ainsi qu’aux interventions
diagnostiques ou thérapeutiques du col de l’utérus (collecte et interprétation du frottis
vaginal, colposcopies, biopsies cervicales et leur interprétation, chirurgie du col de
l’utérus) de 2002 à 2006.
Résultats
Couverture du dépistage en Belgique, les régions et les provinces
La couverture du dépistage du cancer du col de l’utérus, mesurée en 2006, était de
61%. Elle est définie en tant que proportion de la population-cible (femmes entre 25
et 64 ans) ayant eu un frottis du col de l’utérus durant les trois dernières années.
Comme observé lors du rapport précédent, en 1996-2000, les différences de
couverture de dépistage au niveau des régions sont faibles : les couvertures
respectives observées étant de : 60% dans la Région Flamande, 61% à Bruxelles et
63% dans la Région Wallonne. Les différences observées au niveau provincial sont
plus importantes: elles se situent entre 51% (Luxembourg) et 70% (Brabant-Wallon).
Globalement, l’augmentation de la couverture de 2000 à 2006 se limite à 2.2%
L’augmentation est comprise entre 2% dans la Région Flamande, 3% dans la Région
Wallonne, et 4,3% dans la Région de Bruxelles-Capitale. Dans la plupart des
provinces la couverture augmente peu (de 0.9% à 4.3%) sauf au Limbourg et au
Luxembourg où de très faibles diminutions de -0,2% et -0,3% sont observées.
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Group d’âge
Au niveau national, dans les deux groupes les plus jeunes de la population-cible, c. à
d. les femmes de 25 à 34 ans, la couverture est de 70%. A partir de l’âge de 35 ans
jusqu’à 49 ans, la couverture diminue graduellement de 67% à 62%. A partir de 50
ans, la couverture diminue plus rapidement pour atteindre 44% à 60-64 ans. Le profil
d’âge est similaire dans les trois régions, cependant cette diminution en fonction de
l’âge est moins prononcée à Bruxelles et en Région Wallonne.
Statut social
On observe une importante différence de couverture entre les femmes qui bénéficient
ou non d’un remboursement majoré de soins (BIM). Au niveau national, la couverture
de dépistage du cancer du col de l’utérus s’élève à 40% pour les femmes BIM et 64%
pour les non-BIM. Les différences entre les BIM et non BIM se retrouvent à tous les
âges et à tous les niveaux géographiques mais à des hauteurs différentes.
Au niveau régional, la différence varie de 21% à Bruxelles-capitale à 27% en région
flamande. Au niveau provincial, les différences se marquent entre Bruxelles (21%) et
le Brabant-Wallon (33%).
La différence de couverture en fonction du statut social évolue avec l’âge : la
différence entre les BIM et les non-BIM se situe entre 22-25% pour les femmes âgées
de 25 à 44 ans et diminue fortement chez les femmes plus jeunes et plus âgées.
Comparaison aux enquêtes
La couverture évaluée grâce aux fichiers de données des mutuelles est
significativement plus basse que les estimations déduites des enquêtes nationales par
interviews sur la santé. Au niveau national, pour la période 2002-2004 cette
différence est de 11,5%. Une différence similaire était déjà observée dans le rapport
précédent. Cette divergence est probablement due à des biais de rapportage. Selon la
littérature internationale, le statut de dépistage rapporté par l’individu semble
systématiquement surévalué par rapport à la vraie couverture.
Intervalle de dépistage et tranche d’âge cible
L’intervalle modal de dépistage est de 12 à 15 mois. Un laps de temps de trois ans ou
plus n’est observé que chez 5% des femmes avec 2 ou plusieurs frottis pendant la
période de l’étude. Un tiers (30%) des frottis sont répétés dans la même année, cette
proportion diminue avec l’âge.
Dix pourcent de tous les frottis sont prélevés chez des femmes de moins de 25 ans et 8
% chez des femmes âgées de plus de 64 ans.
Collection de frottis par spécialisation médicale
Le pourcentage de frottis prélevés par les médecins généralistes est limité et varie
substantiellement par Région. En 2004-2006, 16% étaient prélevés par les médecins
généralistes dans la Région Flamande, tandis que seulement 7% et 3% l’étaient
respectivement à Bruxelles et dans la Région Wallonne. Le pourcentage de frottis
prélevés par les médecins généralistes diminue au cours du temps, en particulier en
région flamande (26% en 1996 et 14% en 2006).
L’utilisation des frottis
Le nombre de frottis prélevés est théoriquement suffisant pour couvrir plus de 100%
de la population-cible sur un laps de temps de trois ans. En 2006, le rapport entre le
nombre d’interprétations de frottis sur l’effectif moyen de la population-cible, était de
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1.15. Ce rapport devrait être plus élevé si nous étions à même d’ajuster l’effectif de la
population-cible en excluant les femmes qui ont subi une hystérectomie totale.
Néanmoins, seulement 61% des femmes âgées de 25 à 64 ans sont couvertes avec un
ou plusieurs de frottis. En chiffres absolus: 3.2 millions de frottis étaient interprétés
durant la période 2004-2006 mais étaient prélevés chez seulement 1.7 millions de
femmes de 25-64 ans. 1.1 millions de femmes de cet âge n’ont pas eu de frottis.
Coût de la surconsommation de frottis
La surconsommation d’examens cytologiques du col de l’utérus était de 88%, ce qui
signifie que chaque femme examinée a bénéficié d’en moyenne 1.88 frottis sur une
période de 3 ans. L’excès de consommation de frottis était élevé dans toutes les
régions de la Belgique: il était un peu moins élevé dans la Région Flamande (84%), et
les plus élevés dans la Région Capitale de Bruxelles (95%), et dans la Région
Wallonne (94%).
Une partie de cet excès de frottis prestés est utilisée pour le suivi de lésions cervicales
et/ou le suivi après le traitement. En supposant que pour 10% des femmes ayant
réalisé un frottis, deux frottis en moyenne sont nécessaires pour le suivi, on peut
estimer qu’environ 380.000 frottis par an sont exécutés sans contribuer à la couverture
de dépistage ou au suivi.
En chiffres cela correspond à un montant estimé de 7.9 millions € que l’INAMI
rembourse annuellement pour les prélèvements et l’interprétation des frottis avec une
utilité limitée. A ce montant il faut encore ajouter 4.7 millions € pour le dépistage audelà de la tranche d’âge cible.
Utilisation de la colposcopie
Un nombre impressionnant de colposcopies sont exécutées en Belgique. Au niveau
national, en moyenne un examen colposcopique est réalisé pour trois frottis prestés.
Dans la Région Wallonne, le rapport du nombre de frottis sur le nombre de
colposcopies est même inférieur à deux, tandis que dans la Région Flamande ce
rapport est de huit.
La proportion biopsie/colposcopie est basse (en moyenne 5%) ce qui est dû à la très
grande fréquence d’examens colposcopiques chez des femmes sans anomalie de
frottis.
Il est clair que la colposcopie n’est pas utilisée comme recommandé par les guidelines
nationaux et internationaux. L’exploration colposcopique est indiquée dans le cas
d’une première observation de HSIL ou anomalie glandulaire ou après une deuxième
observation de ASC-US ou LSIL ou après un résultat positif de HPV triage dans des
cas de ASC-US et en suivi après des lésions traitées.
Conclusions générales
Les résultats de ce rapport pour les années 2002-2006 sont similaires à ceux du
rapport précédent 1996-2000. La couverture du dépistage du cancer du col d’utérus
en Belgique, définie comme la proportion de femmes dans la tranche d’âge entre 25 et
64 ans ayant reçu un frottis les trois dernières années, n’est que de 61%. Pourtant, le
nombre de frottis prélevés est théoriquement suffisant pour couvrir toute la
population-cible. La couverture en 2006 est seulement 2% plus élevée qu’en 2000.
15
La couverture était considérablement plus bas chez les catégories sociaux vulnérables:
seulement 40% pour les femmes avec statut BIM, tandis que 64% pour les femmes
sans ce statut.
L’estimation de la couverture de dépistage du cancer du col de l’utérus venant
d’enquêtes par interviews, devrait être interprétée avec prudence, étant donné le risque
inhérent de surestimation.
Le prélèvement est surtout une activité de gynécologues, en particulier en Wallonie.
La colposcopie est trop souvent exécutée simultanément au frottis, alors que
l’indication clinique principale de la colposcopie est réservée aux femmes ayant eu
des anomalies cytologiques.
Une réduction structurelle de la sur-utilisation et une redistribution pourrait améliorer
la couverture et en même temps la qualité ce qui pourrait potentiellement résulter en
une augmentation des années de vie sauvées, sans augmentation du financement
public.
Les mesures prévues dans les Recommandations sur le Dépistage du Cancer du
Conseil d’Europe devraient être exécutoires et universelles.
Le manque
d’augmentation de la couverture de dépistage du cancer du col de l’utérus dans les
trois régions démontre la nécessité d’un programme organisé et d’une information
claire des prestataires et des femmes. Les ministères de la santé publique du
gouvernement fédéral et des gouvernements des communautés ainsi que les
représentants des sociétés scientifiques devraient se réunir au plus vite pour définir
une politique de dépistage rationnelle, efficiente et basée sur l’évidence scientifique.
Dans le contexte actuel de dépistage opportuniste, l’organisation d’un programme de
dépistage organisé du cancer du col de l’utérus, devrait répondre aux questions liées
aux problèmes principales identifiés dans ce rapport :
1) Comment peut-on réduire la surconsommation de frottis parmi les femmes
qui participent actuellement au dépistage.
2) Comment peut-on atteindre les 39% de femmes non dépistées et les
convaincre à participer régulièrement (tous les trois ans).
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4. Samenvatting en commentaar
Achtergrond
In 2003 heeft de Europese Raad alle lidstaten van de Unie aanbevolen om
georganiseerde screening voor baarmoedershalskanker aan te bieden aan alle vrouwen
uit de doelgroep. Een optimale dekking of couverture van de doelbevolking is de
sleutel tot een succesvolle opsporingscampagne.
Dit rapport heeft tot doel de reële couverture te evalueren alsook de consumptie van
medische prestaties te meten bedoeld voor opsporing, follow-up of behandeling van
letsels van de baarmoederhals. Hiervoor werd een databestand gebruikt, verkregen
van het Inter-Mutualistisch Agentschap (IMA). Het IMA voegt de informatie van alle
verzekeringsinstellingen in België samen. Het huidige rapport is het tweede in een
reeks en behandelt de periode 2002-2006. Het eerste rapport bestreek de periode
1996-2000.
Deze studie kan gebruikt worden om cervixkankeropsporingsprogramma’s in de
toekomst verder te verbeteren.
Materiaal en methoden
Op vraag van het Wetenschappelijk Instituut Volksgezondheid werd door het IMA
een databestand samengesteld met meer dan 14 miljoen patiënten dossiers. Dit
bestand bevatte informatie van alle medische prestaties geleverd tussen 2002 en 2006,
die verband houden met baarmoederhalskankerscreening, diagnostische en
therapeutische interventies op de baarmoederhals, zoals afname en interpretatie van
cervixuitstrijkjes, colposcopieën, biopsieën van de baarmoederhals en de interpretatie
ervan, alsook chirurgische ingrepen op de baarmoeder(hals).
Resultaten
Dekkingsgraad van de screening in België, de regio’s en de provincies.
In 2006 was de couverture of dekkingsgraad voor baarmoederhalskankerscreening in
België 61%. Onder dekkingsgraad verstaan we het percentage van de doelbevolking,
zijnde vrouwen tussen 25 en 64 jaar, bij wie een cytologisch onderzoek van een
cervixuitstrijk heeft plaatsgevonden minder dan drie jaar geleden. Vergelijkbaar met
het voorgaande rapport, was het verschil in couverture tussen de gewesten gering:
60% in het Vlaamse Gewest, 62 % in het Brussels Hoofdstedelijk Gewest en 63% in
het Waalse Gewest. De verschillen op provinciaal niveau waren groter, gaande van
51% (Luxemburg) tot 70% (Waals-Brabant).
Over het algemeen genomen steeg de screeningscouverture met 2.2% in vergelijking
met 2000. De stijging was het grootst in het Brussels Hoofdstedelijk Gewest (+4.3%)
en tussen 2% en 3% voor de overige twee regio’s. In de meeste provincies steeg de
screeningscouverture in gering mate (tussen 0.9% en 4.3%), met uitzondering van
twee provincies waar een kleine daling werd vastgesteld (Limburg [-0.2%] en
Luxemburg [-0.3%]).
17
Leeftijdsgroepen
De jongste 5-jaar leeftijdsgroepen van de doelgroep, vrouwen van 25-34 jaar oud,
werden het best gescreend met een dekkingsgraad van 70% op nationaal niveau.
Deze verminderde geleidelijk aan van 67% tot 62% bij vrouwen tussen 35 en 49 jaar.
Vanaf de leeftijd van 50 jaar daalde de dekking sneller tot 44% in de leeftijdsgroep
van 60-64 jarigen. Het leeftijdsprofiel was gelijklopend in de drie gewesten. In het
Brussels Hoofdstedelijk Gewest en het Waalse Gewest was deze vermindering in de
oudere leeftijdsgroep enigszins minder uitgesproken dan in het Vlaams Gewest.
Sociale status
Opmerkelijke verschillen werden waargenomen tussen vrouwen met en zonder een
verhoogde terugbetaling voor gezondheidszorg (Rechthebbenden op de Verhoogde
Verzekerings tegemoetkoming (RVV)). In de gehele Belgische doelgroep was de
screeningscouverture respectievelijk 40% en 64% voor vrouwen met en zonder het
RVV statuut. De verschillen tussen de twee sociale categorieën waren consistent over
alle leeftijdsgroepen en de geografische gebieden, maar varieerden in grootte. Op
gewestelijk niveau varieerde het verschil tussen 21% (het Brussels Hoofdstedelijk
Gewest) en 27% (het Vlaams Gewest). Op provinciaal niveau varieerde het verschil
tussen 21% (Brussel) en 33% (Waals-Brabant). Het contrast veranderde ook over de
verschillende leeftijdsklassen: tussen 22% en 25% voor vrouwen van 25-44 jaar en
minder voor jongere en oudere vrouwen.
Vergelijking met de gezondheidsenquête
De dekkingsgraad berekend op basis van gegevens uit het IMA bestand was
aanzienlijk lager dan de schattingen afgeleid uit de nationale gezondheidsenquête. Op
nationaal vlak bijvoorbeeld was dit verschil, voor de periode 2002-2004, 11.5%.
Deze tegenstelling werd reeds waargenomen in het voorgaande rapport en is
waarschijnlijk te wijten aan rapporteringsbiases. Deze vorm van bias is volgens de
internationale literatuur inherent aan enquêtes aan de hand van interviews.
Screeningsinterval en leeftijdsdoelgroepen
Het modaal screeningsinterval was tussen de 12 en 15 maanden. Een tijdsspanne van
36 maanden of meer werd slechts bij 5% van de vrouwen met 2 of meer uitstrijkjes in
de studieperiode waargenomen. Bij 30% van de vrouwen bedroeg het
screeningsinterval minder dan 12 maanden, wat daalde met de leeftijd. Tien procent
van alle geïnterpreteerde uitstrijkjes werden genomen bij vrouwen jonger dan 25 jaar
en 8% bij vrouwen ouder dan 64 jaar.
Afname van uitstrijkjes per type van arts
Het aandeel van huisartsen in de afname van cervixuitstrijkjes was beperkt en
varieerde sterk tussen de gewesten: in 2004-2006, werd 16% van de uitstrijkjes in het
Vlaams Gewest afgenomen door huisartsen, en respectievelijk 7% en slechts 3% in
het Brussels Hoofdstedelijk en het Waals Gewest. Er was een dalende trend over de
periode 2002-2006, vooral in het Vlaams Gewest (26% in 1996 en 14% in 2006).
Intensiteit van het gebruik van uitstrijkjes
Het aantal gebruikte uitstrijkjes was in theorie voldoende om meer dan 100% van de
doelbevolking te dekken over een tijdspanne van drie jaar. In 2006 was de
verhouding tussen het aantal geïnterpreteerde uitstrijkjes t.o.v. de gemiddelde grootte
van de doelbevolking 1.15. Deze verhouding zou hoger moeten zijn indien we de
18
grootte van de doelbevolking konden corrigeren door exclusie van vrouwen die een
volledige hysterectomie hebben ondergaan. Desondanks was slechts 61% van de
doelgroep gedekt met één of meer uitstrijkjes. In absolute cijfers: in de periode 20042006 werden 3.2 miljoen uitstrijkjes geïnterpreteerd, die genomen werden bij slechts
1.7 miljoen vrouwen tussen 25 en 64 jaar oud. Meer dan één miljoen (1.1 miljoen)
vrouwen werden niet onderzocht.
Kosten verbonden aan overscreening
De overconsumptie van cytologische baarmoederhalsonderzoeken was 88%, wat
betekent dat iedere gescreende vrouw 1.88 uitstrijkjes kreeg in een periode van 3 jaar.
Het overmatig gebruik van uitstrijkjes was hoog in alle delen van België. Het was
minder hoog in het Vlaamse Gewest (84%) dan in het Brussels Hoofdstedelijk Gewest
(95%) en het Waalse Gewest (94%).
Het spreekt vanzelf dat een deel van deze “overconsumptie” aangewend werd voor de
follow-up van vrouwen met eerder vastgestelde baarmoederhalsletsels. In de
veronderstelling dat 10% van de gescreende vrouwen gemiddeld twee uitstrijkjes
nodig had voor opvolging van vroegere abnormaliteiten, kunnen we inschatten dat
jaarlijks 380,000 uitstrijkjes afgenomen werden die niet bijdragen tot de
screeningscouverture of tot follow-up. Dit komt overeen met een geschat bedrag van
7.9 miljoen € per jaar die terugbetaald werden door het Rijksinstituut voor Ziekte- en
Invaliditeitsverzekering (RIZIV) voor afname en interpretatie van uitstrijkjes met
beperkt nut. Dit bedrag wordt verder opgedreven met 407 miljoen € voor opsporing
buiten de doelgroep.
Gebruik van colposcopie
Een indrukwekkend aantal colposcopieën werden in België uitgevoerd. Op nationaal
vlak werd er gemiddeld één colposcopie uitgevoerd per drie uitstrijkjes. In het
Waalse Gewest was deze verhouding van het aantal uitstrijkjes tot het aantal
colposcopieën zelfs minder dan twee, terwijl in het Vlaamse Gewest deze verhouding
was acht.
De verhouding aantallen biopsieën/aantallen colposcopieën was laag (gemiddeld 5%)
toe te schrijven is aan het zeer hoge aantal colposcopieën bij vrouwen zonder
afwijkingen van het baarmoederhalsslijmvlies.
Het is duidelijk dat colposcopieën niet gebruikt worden volgens bestaande nationale
of internationale aanbevelingen. Colposcopisch onderzoek is aangewezen in gevallen
van een eerste observatie van HSIL of glandulaire letsels of na een tweede observatie
van ASC-US of LSIL of na een positief HPV triage resultaat (na atypische uitstrijk)
en bij follow-up na behandelde letsels.
Algemene conclusies
De resultaten van het huidig rapport (2002-2006) zijn vergelijkbaar met het
voorgaande (1996-2000). De couverture betreffende baarmoederhalskankeropsporing
in België, gedefinieerd als het percentage van vrouwen in de leeftijdsgroep van 25 tot
64 jaar die een uitstrijkje hebben laten nemen gedurende de laatste drie jaar, was
slechts 61%. Nochtans was het aantal onderzochte uitstrijkjes in theorie voldoende
om de ganse doelbevolking te beschermen. De couverture was 2% hoger in 2006
vergeleken met 2000.
19
De couverture is aanzienlijk lager bij sociaal kwetsbare groepen: amper 40% bij
vrouwen met RVV status en 64% bij vrouwen zonder RVV status.
Schattingen van de couverture afgeleid van enquêtes moeten met voorzichtigheid
geïnterpreteerd worden, gezien het inherente risico op overschatting.
Afname van cervix uitstrijkjes was voornamelijk een activiteit van gynaecologen, in
Wallonië was dit bijna een exclusiviteit.
Colposcopieën werden te vaak uitgevoerd, in vele gevallen wellicht tezelfdertijd als
het routine uitstrijkje, terwijl de belangrijkste klinische indicatie ‘nader onderzoek bij
vrouwen met een vroegere cytologische afwijking’ is.
Een structurele vermindering van de overconsumptie en herinvestering in
couvertureverhoging en kwaliteitsverbetering kan er potentieel toe bijdragen dat er
meer levensjaren gered worden, zonder de nood aan meer publieke middelen.
Maatregelen voorzien in de aanbevelingen voor kankeropsporing van de Europese
Raad zouden bindend en universeel moeten zijn. Het feit dat er nauwelijks een
stijging waar te nemen was in de dekkingsgraad van baarmoederhalskanker screening
over de laatste tien jaar, toont de nood aan van een georganiseerd
screeningsprogramma en duidelijke informatie voor de artsen en de vrouwen. De
federale overheidsdiensten verantwoordelijk voor volksgezondheid en de ministeries
van de gemeenschappen zouden zo snel mogelijk moeten samenkomen, alsook de
vertegenwoordigers van de wetenschappelijke artsenverenigingen, om een rationele
en efficiënte strategie voor de preventie van baarmoederhalskanker te bepalen
gebaseerd op wetenschappelijke evidentie.
In de context van de huidige opportunistische aanpak, zou een georganiseerd
screeningsprogramma voor baarmoederhalskanker een antwoord moeten bieden op
twee cruciale vragen:
(1) Hoe kan de overscreening terug gedrongen worden bij de vrouwen die
momenteel al beschermd zijn door een recent uitstrijkje?
(2) Hoe kunnen de 39% vrouwen die vandaag niet gescreend worden bereikt
worden en overtuigd om een uitstrijkje te laten afnemen om de drie jaar?
20
5. Introduction
In 2006, 604 cases of cervical cancer (European-age standardised rate (E-ASR)
9.9/100,000 women-years) were reported in Belgium, and approximately 264 women
(E-ASR 3.8/100,000 women-years) died from the disease [Belgian Cancer
Registry](1).
The rate of mortality from cervical cancer is not known precisely due to death cause
certification problems. It often happens that for women dying from uterine cancer the
exact topography, cervix uteri or corpus uteri, is not identified. According to a recent
trend analysis, where a tentative solution for this certification problem was proposed,
it was estimated that in the nineties between 300 and 350 women died from cervical
cancer in Belgium each year (2)c.
By well-organised cytological screening, the incidence of cervical cancer can be
reduced to a small residual level (3). This is the key recommendation of the Council
of Europe to all EU member states and of the second edition of the European
Guidelines for Cervical Cancer Screening (4,5). This was already shown to be true in
certain Nordic countries (6) and more recently also in the Netherlands (7,8), United
Kingdom (9) and Norway (10). In Belgium, the official policy is in line with current
European recommendations (5), being 3-yearly screening for the target age group 2564y. However, in Belgium, screening stays essentially opportunistically organised,
resulting in a high level of over screening, and a heterogeneous quality (11). In spite
of the large amount of Pap smears consumed yearly, the impact was lower than
observed in the Nordic countries (12,13). The impact of the Belgian screening on
incidence and mortality cannot be assessed precisely by lack of operational health
information systems, in particular a cervical cytology register linkable to the cancer
registry.
One of the main determinants of success of a screening programme is an optimal
attendance of the target population. Before 1996, screening coverage could only be
measured from interview surveys (14,15).
In Belgium, the whole population is covered by an obligatory health insurance
system. Administrative data registered by sickness funds from their members
constitute a virtually complete source of information on health services delivered to
patients. In 2003, the Scientific Institute of Public Health had received a data file of
more than 13 million records pertaining to medical acts related to cervical cancer
screening and other diagnostic and therapeutic interventions on the uterine cervix that
took place between 1996 and 2000 (16). The data file was compiled by the
Intermutualistic Agency (IMA-AIM) from all seven sickness funds. Analysis of this
data file enabled us to assess to real cervical cancer screening status and the intensity
of the use of Pap smear testing, colposcopies, cervical biopsies, local surgery on the
cervix and hysterectomies (17). The current report assesses a new five-year period
(2002-2006) encompassing more than 14 million records.
c
Readers interested in the evolution of the cervical cancer mortality trend are invited to consult the
website pages of the Unit Cancer Epidemiology of the Scientific Institute of Public Health, available at;
www.iph.fgov/epidemio/epien/prog2.htm.
21
The purpose of this report is to describe the situation with respect to cervical cancer
screening in Belgium up to 2006, at national, regional, provincial and district
(arrondissement) level. The conclusions are useful to optimise future strategies for
organised screening in Belgium, in collaboration with the Communities.
22
6. Material and methods
In 2009, a request was addressed by the Scientific Institute of Public Health to the
IMA/AIM for individual patient data concerning medical acts involving the uterine
cervix for the last five years available.
The IMA/AIM is a non-profit association which has a legal mandate to compile data
from all seven Belgian health insurance agencies concerning delivered medical acts.
Adherence to a health insurance agency is obligatory in Belgium. Because of the
presence of a constant unique identity code, individual patient histories can be traced
and longitudinal analysis is possible.
In 2010, a dataset was received containing approximately fourteen and a half million
records from medical acts, which took place between the 1st of January 2002 and the
31st of December 2006.
The data set contained the following variables: anonymous individual ID code, age,
date of the act, residence and social status of the woman and type of the medical act.
Several data details were truncated to reduce the risk of obtaining unique data in the
cells of cross tables. The age was converted into five-year age group at the exception
of the group 0-14 and the 75+ age groups, which were each grouped into one
category. The calendar date of the act was restricted to the year of performance at the
exception for collection of a Pap smear where also the month of the act was provided.
The residence was converted into the province. The code, province=-99, was given
for women with unknown residence (47,391 records or 0.33% of the database).
Sometimes, province code=+99 was used in case of rare combinations, where
province was censored to avoid identification of women (81,759 records or 0.57% of
the database). The social status was coded as: (1) categories beneficiary of an
increased reimbursement rate [BIR]d, (2) categories with normal reimbursement rate,
(3) social status unknown, and (4) social status censored. The codes for medical acts
were fused into groups as explained in Table 1.
All surgical interventions indicated as group 7, involved total hysterectomies or
removal of the cervix. In this report this group of interventions are identified as total
hysterectomies. No information on subtotal hysterectomy was requested since women
having undergone this intervention are still at risk for cervical cancer.
We assumed that all acts involving the age group 0-14 years were performed on girls
aged 10 to 14 years. Similarly, all acts involving women of 75 years and older were
assumed to be performed in women aged 75-79.
The individual patient data were aggregated over 5-year age groups, calendar years
and geographical area and linked with corresponding population data published by the
Directorate-general Statistics and Economic Information (DGSEI), formerly known as
the National Institute of Statistics (NIS). This allowed computing proportions, rates or
ratios such as the cervical cancer screening coverage, the excess Pap smear use,
hysterectomy incidence rates and the ratio of the number of acts / number of women
concerned.
d
Certain social categories are beneficiary of an increased reimbursement rate (BIR): such as families
with low income, widows, orphans, disabled persons, unemployed persons, retired persons and other
socially vulnerable groups. For a detailed description of the BIR status, see annex 12.1.
23
Table 1. Codes of medical acts included in the data set.
Group
Codes
1
114030-114041
2
3
4
5
6
7
149612-149623
588350-588361
431955-431966
432110-432121
432294-432305
431270-431281
431314-431325
432670, 432681
432736, 432740
431336-431340
431351-431362
431491-431502
432154-432165
Description
Collection of cellular material from the uterine cervix, by
a GP
Collection of cellular material from the uterine cervix, by
a specialist
Microscopic interpretation of a Pap smear (14)
Colposcopy
Biopsy from the uterine cervix
Conisation
Total abdominal hysterectomy
Total vaginal hysterectomy
Vaginal hysterectomy with laparoscopic assistance
Total laparoscopic hysterectomy
Radical hysterectomy (Wertheim)
Total hysterectomy & pelvic lymphadenectomy
Cervix amputation
Removal of residual cervix
For an overview of computed indicators we refer to the glossary in chapter 9.
When coverage over multi-year intervals was computed, women were assumed to
belong to the age group and district at the last medical act concerned.
Statistical methods
The statistical package Stata (10) [Stata Corp, Stata Corporation, Texas, US] was used
for processing and statistical analysis. Analysis consisted in monovariate and
multivariate tabulations, histograms, scatter and line plots. We performed some
ordinary least square linear regressions using population frequency weights and
Poisson regressions, with the logarithm of the population as offset. The strength of
correlations was assessed using Pearson’s or Spearman’s rank correlation coefficients.
Where appropriate, data from the current report (2002-2006) were appended to those
of the previous report (1996-2000), to span a total period of 11 years, with a gap for
the year 2001 for which no data were obtained.
Pap smear testing is assessed at three time intervals, being one, three, and five-year
intervals. The one-year interval corresponds with past and current practice (despite
guidelines). A three-year interval is recommended and the five-year interval allows
for international comparison.
Three different geographical levels were considered for analysis: the whole of
Belgium, the 3 regions (Flemish, Walloon and Brussels-Capital Region) and the 11
provinces. Contrary to the previous report, no information was obtained for the level
of the 43 districts (arrondissements). This was due to the fact, that for the current
report more detail was provided regarding the date of Pap smear collection (month
and year of the act), whereas, for the period 1996-2000, only the year of the act was
obtained. This allowed computation of the interval between successive Pap smears
with a higher level of precision.
24
Given the large populations involved, it was generally inappropriate to report 95%
confidence intervals, since upper and lower bounds were nearly equal.
For the computation of the cumulative incidence until a given age k, the following
formula was applied: Cumulative Incidence = 1 – Πk(1-eai . ΔT), where Π stands for
cumulative product, ai for age specific incidence, and ΔT for the amplitude of the age
categories (18).
Age-standardised coverage ratios (A-SCR) were calculated, using the national agespecific coverage rates in 2006 as reference, which adjusts for differences in age
composition. Also age-standardised coverage rates were computed by using the
truncated European standard population as a reference (19).
25
7. Results
The received data file contained more than 14 million records. The distribution by
type of medical act is shown in Table 2.
Table 2. Number of individual acts pertaining to Pap smears, colposcopies, biopsies and surgical
interventions on the uterine cervix performed in Belgium in the period 1996-2000 and 2002-2006.
Act
Collection of Pap
smear by GP
Collection of Pap
smear by specialist
Total hysterectomy or
cervix amputation
Colposcopy
Biopsy of the cervix
Conisation of cervix
Interpretation of Pap
smear
Total
Period 1:
1996-2000
Frequency
%
Period 2:
2002-2006
Frequency
%
Difference:
period 2-period 1
N
%
815,782
6.18
593,880
4.18
-221,902
-27.20
4,435,416
33.57
4,991,413
35.17
+555,997
12.54
84,564
2,009,956
106,138
24,445
0.64
15.21
0.80
0.19
83,542
1,980,927
93,773
32,182
0.59
13.96
0.66
0.23
-1,022
-29,029
-12,365
+7,737
-1.21
-1.44
-11.65
31.65
5,734,201
13,210,502
43.41
100
6,417,936
14,193,653
45.22
100
+683,735
11.92
In this report, we will address subsequently the cytological interpretation of Pap
smears (subchapter 7.1); the screening coverage by social status (subchapter 7.2), the
type of physician who takes Pap smears (subchapter 7.3); the interval between
successive Pap smears (subchapter 7.4); colposcopy and taking cervical biopsies
(subchapter 7.5); hysterectomy (subchapter 7.6) and finally the interpretation of Pap
smears in women after a recent hysterectomy (subchapter 7.7)e.
7.1. Cytological interpretation of Pap smears of the uterine
cervix
7.1.1. National level
In total, about 6.4 million smears were interpreted in the period 2002-2006 or a yearly
average of over 1.3 million (see Table 3). The total number of smears/year rose
nearly linearly (R2=0.96) between 2002 and 2004 with an increase of approximately
17 600 additional examinations per year. This corresponds to an average yearly
increase of 2.8 % (according to a linear regression model). Since 2004, the number of
Pap smears interpreted by year did not increase any more (slope not statistically
significantly different from zero, R2= 0.05).
e
72,757 records regarding pathological interpretations of tissue specimen from the period 1996-2000
and 270,315 from the period 2002-2006 were excluded from the study. The specimen from the 1st
period did not cover all cervical biopsies, conisations and total hysterctomies/cervixamputations and
those from the 2nd period included also other organs.
26
Table 3. Total number of Pap smears interpreted by year (Belgium, 2002-2006).
Year
2002
Frequency
1,258,881
Percent
19.6
Cumulative
percent
19.6
2003
1,270,521
19.8
39.4
2004
1,294,178
20.2
59.6
2005
1,299,050
20.2
79.8
2006
1,295,306
20.2
100.0
Total
6,417,936
100
The distribution per 5-year age group is shown in Table 4. The proportion of smears
from women in the 25 to 64 year target age group was 82.2%. Respectively 10.1%
and 7.7% of Pap smears were taken from women who were younger or older.
Table 4. Total number of Pap smears by 5-year age group (Belgium, 2002-2006).
Age group
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
≥ 75
Total
Frequency
2,919
146,708
498,375
704,465
790,455
810,657
801,194
727,865
623,750
495,633
322,477
236,194
147,013
110,231
6,417,936
Percent
0.1
2.3
7.8
11.0
12.3
12.6
12.5
11.3
9.7
7.7
5.0
3.7
2.3
1.7
100
Cumulative
percent
0.1
2.3
10.1
21.1
33.4
46.0
58.5
69.9
79.6
87.3
92.3
96.0
98.3
100.0
The time interval between two successive smears for women having at least two
smears between 2002 and 2006 is shown in Table 5 and Figure 1.
A detailed picture of the real interval was not possible since the dates of smears were
truncated at the calendar year. Nevertheless, given this limitation, the modal came out
strongly at the one-year interval (in 63% of the cases, when women with only one Pap
smear were excluded). In 10% there was less than one year between successive
smears. A more detailed description of the screening interval can be found in
subchapter 7.3 regarding collection of Pap smears where besides the year also the
month of the act was provided.
27
Table 5. Distribution of the time interval between two successive smears (rounded at one year),
(Belgium, 2002-2006).
Interval
(“only one smear” included)
Cumulative
Frequency Percent frequency
404,065
6.3
6.3
2,470,650
38.5
44.8
826,202
12.9
57.7
201,995
3.2
60.8
45,010
0.7
61.5
2,470,014
38.5
100.0
6,417,936
100
(years)
0
1
2
3
4
missingf
Total
(“only one smear” excluded)
Cumulative
Frequency Percent
percent
404,065
10.2
10.2
2,470,650
62.6
72.8
826,202
20.9
93.7
201,995
5.1
98.9
45,010
1.1
100.0
3,947,922
100
60
Percent
40
20
0
0
1
2
Interval (Years)
3
4
Figure 1. Histogram of the distribution of average time interval between two successive smears,
(Belgium, 2002-2006).
In total 2,470,014 women had only one smear in the observed time interval (20022006), and hence no time interval can be calculated for these women. The year that
their last smear took place is relevant to complete the information on the screening
interval and is shown in Table 6.
f
Missing: no interval can be computed for women having only one Pap smear in the surveyed period.
28
Table 6. Distribution of the years where the last smear of a woman took place (Belgium, 2002-2006).
Year
2002
2003
2004
2005
2006
Total
Frequency
151,068
198,494
306,249
597,934
1,216,269
2,470,014
Percent
6.1
8.0
12.4
24.2
49.2
100
Cumulative
percent
6.1
14.2
26.6
50.8
100.0
The distribution of the total number of smears per woman within the period 20022006 is displayed in Table 7. The average number of smears per screened woman
was 2.6, with a range of 1 to 45. Almost 8 percent of screened women had more than
5 Pap smear interpretations in the five-year period.
Table 7. Distribution of the total number of smears taken from the same women (Belgium, 20022006).
Cumulative number of
smears per woman
1
2
3
4
5
6
7
8
9
>=10
Total
Number of
women
745,821
590,349
470,392
363,367
226,513
45,851
14,809
6,413
3,404
3,095
2,470,014
% of women
with Pap
smears
11.6
18.4
22.0
22.7
17.7
4.3
1.6
0.8
0.5
0.5
100,0
Cumulative
percent
11.6
30.0
52.0
74.7
92.3
96.6
98.2
99.0
99.5
100.0
29
7.1.1.1
Use of cervical cytology at yearly intervals
The evolution of the one-year screening coverage and the consumption of Pap smears
over time is shown in Table 8. In Figure 2, data from the previous study were added
to show the trend over 11 years (from 1996-2006). The coverage (full line curve, red)
increased with 3.5% between 1996 and 1998, from 29.9% to 33.4 %. From then
increase slowed down: 1.2% increase between 1998 and 2003, and no further increase
thereafter. The #smears/#women ratio (green curve, interrupted line) was 2 to 3%
higher than the screening coverage.
Table 8. Consumption of Pap smears and one-year screening coverage between 2002 and 2006 for
women between 25 and 64 years old.
Year
2002
2003
2004
2005
2006
Number of women
25-64 years
2,741,601
2,755,767
2,767,971
2,782,136
2,806,442
Number of
smears
1,038,028
1,043,990
1,062,223
1,067,024
1,065,231
Number of women
screened
971,726
977,596
993,009
999,875
999,747
1-year
coverage
35.4%
35.5%
35.9%
35.9%
35.6%
#smears /
#women ratio
0.38
0.38
0.38
0.38
0.38
45%
40%
35%
30%
%
25%
20%
15%
10%
Coverage, 1 year interval
# smears / # women
5%
0%
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Year
Figure 2. Evolution of the one-year screening coverage and of the #smears/#women ratio (Belgium,
1996-2006, women aged 25-64 years).
The screening coverage considering a one-year interval varies strongly by age group
(see red curves, shown for four years, in Figure 3). The coverage increases rapidly to
reach a maximum of more than 35 % in the age group 30-34 years. From this age the
coverage declines slowly until around 30% in the age group 50-54 years. The
coverage decreases rapidly after the age of 55. The four graphs look very similar. The
age-specific screening coverage changed hardly over time, as shown by overlapping
curves in Figure 4.
30
Belgium , 2003
Belgium , 2004
.4
.4
.2
.2
0
0
10
20
30
40
age
50
60
10
70
Belgium , 2005
20
30
40
age
50
60
70
30
40
age
50
60
70
Belgium , 2006
.4
.4
.2
.2
0
0
10
20
30
40
age
50
60
70
10
20
Figure 3. Variation of the screening coverage (red full line) and the # smears / # women ratio (green
interrupted line) considered over a 1-year interval according to 5-year age group and by year.
2002
2006
2004
1-year coverage
.4
.2
0
10
20
30
40
50
Age group
60
70
Figure 4. Relation between the one-year coverage and age group in the years 2002, 2004 and 2006.
31
7.1.1.2
Use of cervical cytology at 3-year intervals
The consumption of Pap smears and the coverage built up over a three-year period is
illustrated in Table 9. The number of smears used was sufficient to cover more than
100% of the target population since the ratio of the number of smears taken in women
between 25 and 64 years surpasses the average number of women of that age living in
Belgium (#smears/#women ratio > 1). Nevertheless the 3-year coverage was only
61%. Eighty eight percent of smears did not contribute to the population coverage,
since they are used to screen women who were already screened within the 3-year
period concerned. Of course, a part of this “excess use” is used for follow-up of
women with previous cervical abnormality. Assuming that 10 % of the screened
women needed on average two follow-up Pap smears, we can estimate that yearly
about 380,000 Pap smears are taken that do not contribute to screening coverage or
follow-up. This corresponds with an estimated amount of € 7.9 million per year
reimbursed by the National Institute for Health and Disability Insurance (NIHDI) for
taking and reading Pap smears with limited utility. This amount is further increased
with € 4.7 million for screening beyond the target age range. (see annex 12.2 for
calculation of the Pap smears with limited utility and their associated costs for
NIHDI).
Table 9. Consumption of Pap smears, three-year screening coverage and excess use between 2002 and
2006 for women between 25 and 64 years old (Belgium).
Period
2002-2004
2004-2006
Number of women
#smears/
Mean female
3-year #women
Number of screened <3years
population
ago coverage
ratio Excess use
(25-64 years) smears takeng
2,755,113
3,140,748
1,671,840
60.7%
1.14
87.9%
2,785,516
3,199,984
1,706,043
61.2%
1.15
87.6%
The 3-year screening coverage, reached a maximum of 70% in women of 25-34 years.
It decreased gradually until 57% in the 50-54 year age group. Thereafter the coverage
declined more rapidly. In the age group 25 to 54 years, more smears were taken than
what was necessary to cover 100% of the population (green curve surpasses the
horizontal line through unity). The age relation for the year 2004 was similar (data
not shown).
g
Only smears taken in the age group 25-64 years were considered.
32
# smears/# women ratio
Coverage, 3-year interval
1.4
1.2
1
.8
.6
.4
.2
0
10
20
30
40
Age
50
60
70
Figure 5. Variation of the cervical cancer screening coverage and the # smears / # women ratio
considered over a 3-year interval according to 5-year age group (Belgium, 2006).
The excess Pap smear use in relation to age is plotted in Figure 6. The excess was
higher than 80% from the age of 25 to 69 and reached a maximum of 92% in the age
group 50-54.
Extra smears/screened woman
1.5
1
.5
0
10
20
30
40
Age
50
60
70
Figure 6. Excess Pap smear use as a function of age group (Belgium, 2006).
33
7.1.1.3
Evolution of 3-year screening coverage between 19962006
In order to evaluate the trend of the cervical cancer screening coverage over the
longest possible period, we compiled data from a previous report covering 1996-2000
with the current data set. Four 3-year periods were considered over which screening
coverage could be computed: 1996-1998, 1998-2000, 2002-2004, 2004-2006. An
ordinary least square linear regression was performed to assess changes over time.
The linear regression took the form of (Coveragey=A+B*year), where A is the
constant (representing the coverage at the beginning of the data set), B equals the
slope or change in screening coverage per year and Y is the year-1996. On average,
the coverage increased only by 0.58% per year (95% CI: 0.21%-0.95%) (see Table 10
and Figure 7). The number of smears contributing to coverage computed over the 3years was used as a frequency weight.
Table 10. Change in 3-year screening coverage between 1996-2006, computed by linear regression.
Slope
0.58%
Belgium
Coverage in 2006
Observed
Fitted
61.25%
61.59%
Observed
Difference
-0.34%
Fitted
.8
.75
Screening coverage
.7
.65
.6
.55
.5
.45
.4
1998
2000
2002
year
2004
2006
Figure 7. Trend of three year-coverage for cervical cancer screening among 25-64 year old women
evaluated in the years 1998, 2000, 2004 and 2006, (Belgium, 1996-2006).
Observed values: green circles; fitted values: red line (linear regression).
34
7.1.1.4
Use of cervical cytology at a 5-year interval
The consumption of Pap smears and the coverage built up over five-year periods is
illustrated in Table 11. In total 5.4 million smears were interpreted between 2002 and
2006 from 2.0 million women in the age group 25-64. The number of smears used
was sufficient to cover 193% of the target population. Nevertheless the 5-year
coverage was only 71%. Screened women received on average 1.71 additional
smears they do not need if a 5-year screening policy should be adapted.
Table 11. Consumption of Pap smears, five-year screening coverage and excess use between 2002 and
2006 for women between 25 and 64 years old.
Mean female
population
(25-64 years)
2,770,785
Period
2002-2006
Number of
smears taken
5,356,607
Number of women
screened <5years
ago
1,974,606
5-year
coverage
71.3%
#smears/
#women
ratio Excess use
1.93
71.3%
The 5-year screening coverage in 2006 reached a maximum of 79 % in women 25-34
year old (see Figure 8). It decreased gradually until 67 % in the 50-54 year age group.
Thereafter the coverage declined more rapidly. In the age groups 25-44, the amount
of smears used could cover the population twice.
Cytological screening for cervical cancer
Belgium, 2006
2.5
2
1.5
1
.5
0
10
20
30
40
Age
50
60
70
Figure 8. Variation of the screening coverage and the # smears / # women ratio considered over a 5year interval according to 5-year age group (Belgium, 2006).
35
7.1.2. Regional level
7.1.2.1
Use of cervical cytology at yearly intervals
The evolution of 1-year screening coverage and Pap smear use over the period 2002
to 2006, for 25-64 year old women is shown in Table 12 for the three regions. The
differences between the regions were small. In 2006, the 1-year coverage was highest
in the Walloon Region (37.6%), followed by the Brussels-Capital Region (35.6%).
The coverage was lowest in the Flemish Region (34.4%). Figure 9 displays the trend
of the 1-year coverage for each region over a period of 11 years (1996-2006).
Table 12. Consumption of Pap smears and one-year screening coverage between 1996 and 2000 for
women between 25 and 64 years old, by region.
Region Year
2002
2003
Flemish
Region 2004
2005
2006
Brussels 2002
2003
Capital 2004
Region
2005
Number of women Number of
Number of
1-year
#smears/
25-64 years
smears women screened coverage #women ratio
1,594,574
571,917
539,290
33.8%
0.359
1,600,468
574,203
541,464
33.8%
0.359
1,605,679
586,280
552,034
34.4%
0.365
1,612,498
588,662
555,417
34.4%
0.365
1,624,676
591,722
558,910
34.4%
0.364
263,078
106,449
97,043
36.9%
0.405
267,517
109,100
99,532
37.2%
0.408
270,975
110,498
100,735
37.2%
0.408
273,492
109,349
100,278
36.7%
0.400
2006
2002
Walloon 2003
Region 2004
2005
2006
277,686
883,949
887,782
891,317
896,146
904,080
107,558
350,598
353,284
359,201
362,860
359,337
98,951
327,247
330,015
334,786
338,769
336,055
35.6%
37.0%
37.2%
37.6%
37.8%
37.2%
0.387
0.397
0.398
0.403
0.405
0.397
40%
35%
Coverage
30%
25%
20%
15%
10%
Flemish Region
Brussels
5%
0%
1996
Walloon Region
1997
1998
1999
2000
2001
2002
2003
2004
2005
Year
Figure 9. Evolution of the one-year screening coverage between 1996 and 2006, by region.
36
2006
In Figure 9, over the first five years, a small increase of the coverage was noted in the
three regions (+4.1%, +6.3% and 3.9%, in the Flemish, Brussels-Capital and Walloon
Region, respectively). In the period 2002-2006, the trend became nearly horizontal in
the Flemish and Walloon Region (+0.6%, 0.1%), whereas in the Brussels-Capital
Region the trend became slightly negative (-1.2%).
Figure 10 illustrates the relation between age and Pap smear consumption and the 1year coverage for the year 2000. A maximum coverage was reached in the 30-34 year
age group, respectively at 39%, 37% and 40% in the Flemish, Brussels-Capital and
Walloon Region. Remarkable was that the coverage remains at a plateau until the age
of 54 years in the Brussels-Capital Region and that it only decreased slowly until this
age in the Walloon Region. However, in the Flemish Region, the coverage dropped
more quickly. The coverage in age group 50-54 year was respectively 31, 32% and
37% in the Flemish, Brussels-Capital and Walloon Region. From the 55-59 year age
group the coverage declined quickly in the Flemish and Walloon region. From this
age on, the coverage was highest in the Brussels-Capital Region.
2006
Flemish Region
Brussels
.6
.4
.2
0
10 20 30 40 50 60 70
Walloon Region
.6
.4
.2
0
10 20 30 40 50 60 70
Age group
Figure 10. Variation of the screening coverage and the # smears / # women ratio considered over a 1year interval according to 5-year age group, by region (Belgium, 2006).
37
7.1.2.2
Data concerning the consumption of Pap smears and the screening coverage
considered over a 3-year interval are documented in Table 13 for the three regions.
The coverage was similar in the three regions. It was highest in the Walloon Region
(63.3% in 2006), which was respectively 1.4% and 3.3% higher than in the BrusselsCapital and the Flemish Region. The increase over the whole period was 0.8% for the
Flemish Region and 0.5% for the Walloon Region. In the Brussels-Capital Region, a
slight decrease of 0.4% was noted. The #smear/#women ratio was always higher than
one. The excess use of Pap smears among screened women was always above 80%.
It was highest in the Brussels-Capital Region (97% and 95%) and was lowest in the
Flemish Region (84%).
Table 13. Consumption of Pap smears, three-year screening coverage and excess use between 2002
and 2006 for women between 25 and 64 years old, by region.
Number of Number of women
#smears/
3-year #women
smears screened <3years
taken
ago coverage
ratio
59.2%
1,742,417
947,756
1.09
60.0%
1,778,783
968,385
1.10
Period
Region
2002-2004 Flemish
2004-2006 Region
Mean female
population
(25-64 years)
1,600,240
1,614,285
2002-2004 Brussels
2004-2006
267,190
274,052
328,664
330,150
166,451
169,654
62.3%
61.9%
1.23
1.20
97%
95%
2002-2004 Walloon
2004-2006 Region
887,683
897,182
1,069,667
1,091,051
557,633
568,004
62.8%
63.3%
1.21
1.22
92%
92%
Excess
use
84%
84%
The differentiation of the screening coverage and Pap smear consumption by age is
illustrated in Figure 11, for the latest 3-year period. A maximum coverage was
reached at the age of 25-34 years. This was 69% in the Flemish Region (in age group
25-34), 69% in the Brussels-Capital Region (in age group 30-34) and 73% in the
Walloon Region (in age group 25-29). The decline in coverage by age after 35 years
was slow until the 50-54 year age group in the last two regions. In the 50-54 year age
group the 3-year coverage was respectively 55%, 59% and 60% for the Flemish,
Brussels-Capital and Walloon Region. After the age of 50 the coverage was highest
in the Brussels-Capital Region.
In the Flemish Region, the #smears/#women ratio was higher than 1 in the age range
25 to 59, in the Brussels-Capital Region in the range 25-64 years, and in the Walloon
Region in the range 20-59 years.
The excess smear use as a function of age is plotted in Figure 12. The excess was
maximal in the age groups 50-59: 89% in the Flemish Region (age group 50-54),
102% in the Brussels-Capital Region (age group 55-59) and 97% in the Walloon
Region. The excess use was highest in the Brussels-Capital and lowest in the Flemish
Region (age group 55-59).
38
Flemish Region
Brussels
1.4
1.2
1
.8
.6
.4
.2
0
10 20 30 40 50 60 70
Walloon Region
1.4
1.2
1
.8
.6
.4
.2
0
10 20 30 40 50 60 70
Age
Figure 11. Variation of the screening coverage and the # smears / # women ratio considered over a 3year interval according to 5-year age group (Belgium, by region, 2006).
Extra smears/screened woman
120%
100%
80%
Flemish Region
60%
Brussels
Walloon Region
40%
20%
0%
10
20
30
40
50
60
70
Age group
Figure 12. Excess Pap smear use as a function of age (Belgium, by region, 2006).
39
7.1.2.3
Evolution of 3-year screening coverage between 19962006
The trend in the 3-year screening coverage was studied by linear regression, including
an interaction term (region*year). The increase in coverage was slightly greater in the
Brussels-Capital Region: slope of 1.1% per year and similar (0.6%) in the two other
regions (see Table 14 and Figure 13 ). However, in the Brussels-Capital Region the
increase slowed down in the latest period as indicated by the difference between
observed and fitted rates observed in 2006.
(Belgium, by region, 1996-2006).
Coverage in 2006
Slope
Observed
0.59%
60.0%
1.10%
61.9%
0.58%
63.3%
Region
Flemish Region
Brussels
Walloon Region
Fitted
60.3%
63.1%
63.7%
Observed
Fitted
Flemish Region
Screening coverage
Difference
-0.3%
-1.2%
-0.4%
Brussels
.8
.75
.7
.65
.6
.55
.5
.45
.4
1998
Walloon Region
2000
2002
2004
2006
.8
.75
.7
.65
.6
.55
.5
.45
.4
1998
2000
2002
2004
2006
Year
Figure 13. Three-year coverage for cervical cancer screening among 25-64 year old women evaluated
in the years 1998, 2000, 2004 and 2006, by region. Observed values (green circles) and fitted values
(linear regression: red line).
7.1.2.4
Use of cervical cytology at a 5-year interval
Screening parameters computed over a 5-year period at the region level are not
reported here.
40
7.1.3. Provincial level
We limit the analysis at the provincial level to screening over a 3-year interval.
7.1.3.1
The screening parameters at 3-year intervals are documented for 2 periods (2002-2004
and 2004-2006) for all the provinces in Table 15.
Table 15. Consumption of Pap smears, three-year screening coverage, excess use and increase in
linear trend of the coverage between 2002 and 2006 for women between 25 and 64 years old, by
province.
Period
Province
2002-2004 Antwerp
2004-2006
Number of
Mean female Number of
women
#smears
screened
3-year /#wome Excess
smears
population
use
taken <3years ago coverage n ratio
(25-64 years)
441,301
483,864
266,816
60.5%
1.10
81%
445,682
496,663
274,185
61.5%
1.11
81%
2002-2004 Brussels
2004-2006
267,190
274,052
328,664
330,150
166,451
169,654
62.3%
61.9%
1.23
1.20
97%
95%
2002-2004 Flemish2004-2006 Brabant
279,302
281,850
331,636
335,484
176,347
179,758
63.1%
63.8%
1.19
1.19
88%
87%
2002-2004 Walloon2004-2006 Brabant
96,778
98,305
139,730
140,603
67,752
68,798
70.0%
70.0%
1.44
1.43
106%
104%
2002-2004 West2004-2006 Flanders
293,841
294,911
304,425
309,961
166,175
169,534
56.6%
57.5%
1.04
1.05
83%
83%
2002-2004 East2004-2006 Flanders
366,797
370,033
411,315
423,438
215,924
222,262
58.9%
60.1%
1.12
1.14
90%
91%
2002-2004 Hainaut
2004-2006
340,017
342,860
393,722
402,053
207,599
210,840
61.1%
61.5%
1.16
1.17
90%
91%
2002-2004 Liège
2004-2006
270,446
272,619
336,992
342,604
176,775
179,624
65.4%
65.9%
1.25
1.26
91%
91%
2002-2004 Limburg
2004-2006
219,000
221,810
211,177
213,237
122,494
122,646
55.9%
55.3%
0.96
0.96
72%
74%
2002-2004 Luxem2004-2006 bourg
63,133
64,394
59,241
61,341
32,112
33,100
50.9%
51.4%
0.94
0.95
84%
85%
2002-2004 Namur
2004-2006
117,309
119,001
139,982
144,450
73,395
75,642
62.6%
63.6%
1.19
1.21
91%
91%
41
The 3-year screening coverage in the target population reached in 2006, and ranked
from highest to lowest is shown in Table 16. In spite of small contrasts between the
regions, substantial differences between the provinces were observed in coverage and
excess use. The coverage range between the highest and the lowest ranking province
was 28.6%. The screening coverage was highest in Walloon-Brabant (70.0%) and
lowest in Luxembourg (51.4%). Table 16 also shows the age-standardised coverage
ratio (A-SCR), using the national age-specific coverage rates as reference, which
adjusts for interprovincial differences in age composition. The ranking in A-SCR was
nearly equal to the crude 3-year coverage at the exception of minor differences in the
ranks of Brussels, Antwerp and Hainaut.
Table 16. Three-year coverage of cervical cancer screening in 2006 among 25-64 year old women, by
province, ranked from highest to lowest.
Province
Walloon-Brabant
Liège
Flemish-Brabant
Namur
Brussels
Antwerp
Hainaut
East-Flanders
West-Flanders
Limburg
Luxembourg
3-year coverage
in 2006
70.0%
65.9%
63.8%
63.6%
61.9%
61.5%
61.5%
60.1%
57.5%
55.3%
51.4%
Age-standardised
coverage Ratio
1.15
1.08
1.04
1.04
0.99
1.01
1.01
0.98
0.95
0.90
0.83
Figure 14 shows the relation between coverage and #smears/#women ratio on the one
hand and age group on the other hand, by province. The corresponding tables can be
found in annex 12.3. We can remark that the high coverage reached in the age group
25-34 was maintained over a longer age range in Brussels and the Walloon provinces
than in the Flemish provinces where the coverage tended to decrease slightly more
rapidly by age after having reached the maximum.
The gap between the green curve and red curve in Figure 14 illustrates the amount of
over-screening.
The excess smear use varied between 72% (Limburg, 2004) and 104% (WalloonBrabant, 2004) (see Table 15). This means that each covered women received on
average between 1.72 and 2.04 smears over a period of 3 years.
42
Antwerpen
Brussels
Flemish-Brabant
Walloon-Brabant
10 20 30 40 50 60 70
10 20 30 40 50 60 70
West-Flanders
East-Flanders
Hainaut
Liège
10 20 30 40 50 60 70
10 20 30 40 50 60 70
Limburg
Luxembourg
1.6
1.2
.8
.4
0
1.6
1.2
.8
.4
0
1.6
1.2
.8
.4
0
1.6
1.2
.8
.4
0
1.6
1.2
.8
.4
0
Namur
10 20 30 40 50 60 70
1.6
1.2
.8
.4
0
10 20 30 40 50 60 70
Age group
Figure 14. Three-year interval Pap smear coverage, smears/women ratio, by 5-year age group and by
province (Belgium, 2006).
43
Evolution of the 3-year screening coverage between 1996-2006
The evolution of the 3-year screening coverage between 1996 and 2006 in each
province is shown in Table 17 and Figure 15. The slope of the linear regression
including the (province*year) interaction was greatest in Brussels (slope=1.10%),
followed by Antwerp (0.79%), Hainaut and Namur (both 0.70%). In Limburg, the
trend was nearly horizontal (slope=0.02%).
(Belgium, by province, 1996-2006).
Province
Antwerp
Brussels
Flemish-Brabant
Walloon-Brabant
West-Flanders
East-Flanders
Hainaut
Liège
Limburg
Luxemburg
Namur
44
Slope
0.79%
1.10%
0.48%
0.31%
0.67%
0.68%
0.70%
0.55%
0.02%
0.17%
0.70%
Coverage in 2006
Observed
61.5%
61.9%
63.8%
70.0%
57.5%
60.1%
61.5%
65.9%
55.3%
51.4%
63.6%
Fitted
61.8%
63.1%
64.0%
70.3%
57.7%
60.3%
62.0%
66.2%
55.6%
51.5%
63.8%
Difference
-0.3%
-1.2%
-0.3%
-0.4%
-0.2%
-0.2%
-0.5%
-0.3%
-0.3%
-0.1%
-0.2%
Screening coverage
Observed
Brussels
Flemish-Brabant
Walloon-Brabant
.8
.75
.7
.65
.6
.55
.5
.45
.4
.8
.75
.7
.65
.6
.55
.5
.45
.4
1998
Screening coverage
Fitted
Antwerpen
2000
2002
2004
2006
1998
West-Flanders
East-Flanders
Hainaut
Liège
2002
2004
2006
2002
2004
2006
2002
2004
2006
.8
.75
.7
.65
.6
.55
.5
.45
.4
.8
.75
.7
.65
.6
.55
.5
.45
.4
1998
2000
2002
2004
1998
2006
Limburg
Screening coverage
2000
2000
Luxembourg
.8
.75
.7
.65
.6
.55
.5
.45
.4
1998
Namur
2000
.8
.75
.7
.65
.6
.55
.5
.45
.4
1998
2000
2002
2004
2006
Year
Figure 15. Three year-coverage for cervical cancer screening among 25-64 year old women evaluated
in the years 1998, 2000, 2004 and 2006, by province: observed values (green circles) and fitted values
(linear regression: red line).
45
7.2. Screening coverage by social status
7.2.1. BIR status
The social status (BIR: beneficiary of increased reimbursement)) was available for the
period 2002-2006. The BIR status was coded as 0 (normal status) or as 1 (vulnerable
status). The distribution of the BIR status varied by age group, by region and by
province, but was rather constant by calendar year. The variation in the proportion of
women with BIR=1 is shown in Figure 16 for the whole of Belgium and the three
regions and, in Figure 17, for the Flemish and Walloon provinces, respectively.
0.6
Proportion BIR=1
0.5
0.4
Belgium
Flemish Region
Walloon Region
Brussels
0.3
0.2
0.1
0
15
20
25
30
35
40
45
50
55
60
65
70
75
Age group
Figure 16. Proportion of women entitled to the benefit of increased reimbursement (BIR), by age
(Belgium and the three regions, 2006).
0.6
0.6
Antw erp
West-Flanders
0.5
Limburg
Proportion BIR=1
Proportion BIR=1
East-Flanders
0.4
Hainaut
Liège
0.5
Flemish-Brabant
0.3
0.2
0.1
Luxembourg
Namur
0.4
Walloon-Brabant
0.3
0.2
0.1
0
0
15
20
25
30
35
40
45
50
Age group
55
60
65
70
75
15
20
25
30
35
40
45
50
55
60
65
70
Age group
Figure 17. Proportion of women entitled to the benefit of increased reimbursement (BIR), by age
(Flemish provinces at left and Walloon provinces at right, 2006).
46
75
The shape of the age curve was similar in all provinces and regions with a slight
decrease over the range 15-29 years, a slight increase in the range 30-44, followed by
a steep increase for women of 45 and older. The proportion of women with special
BIR status was highest in the Brussels-Capital Region, intermediate in the Walloon
Region and lowest in the Flemish Region.
47
7.2.2. 3-year interval screening coverage by BIR status
Table 18 shows the screening coverage, the #smears / #women ratio and the excess
use of cervical cytology in both social categories (BIR=0 and BIR=1) for women aged
25-64 years at all geographic levels. The last two columns display the contrasts in
screening coverage between the two social categories as ratios (BIR=1 / BIR=0) and
as absolute differences (BIR=1 - BIR=0), respectively. The screening coverage was
lower among women with special BIR status (ratios consistently <1 and differences
between 21 and 33%). The screening coverage at Belgian level was 64.0% and 40.1%
in women with normal and special social status, respectively (ratio=0.63;
difference=24%).
At regional level, screening coverage varied between 62.9% and 69.0% (for women
with BIR code=0) and between 35.7% and 48.2% (for women with BIR code=1). The
highest coverage rate was noted in Brussels. The lowest rate was noted in the Flemish
Region, where the contrast between the two social categories were most extreme
(ratio = 0.57, difference = 27%).
Table 18. Three-year screening coverage, #smears/#women ratio, excess use and ratio of coverageBIR=1
/ coverageBIR=0 and difference of coverageBIR=1 - coverageBIR=0 among women aged 25-64 year for the
whole of Belgium, regions and provinces.
BIR=0
Area
Belgium
3-year
coverage
64.0%
#smears/
#women
ratio
1.21
Contrast 3-y
coverage
BIR=1
Excess 3-year
use
coverage
88.9% 40.1%
#smears/
#women
ratio
0.68
Excess use Ratio Difference
68.9%
0.63
23.9%
Regions
Flemish
Region
Brussels
Walloon
Region
Antwerp
WestFlanders
EastFlanders
Hainaut
Liège
Limburg
Luxembourg
Namur
Brussels
FlemishBrabant
WalloonBrabant
48
62.5%
69.0%
1.15
1.36
84.7%
97.2%
35.7%
48.2%
0.58
0.84
62.6%
74.6%
0.57
0.70
26.8%
20.8%
67.5%
1.31
93.7%
42.5%
0.73
72.5%
0.63
25.0%
Provinces
63.9%
1.17
82.3%
39.0%
0.63
60.4%
0.61
24.9%
59.7%
1.10
83.9%
32.5%
0.53
61.8%
0.54
27.2%
61.8%
65.1%
69.8%
59.9%
1.18
1.25
1.34
1.05
91.6%
92.3%
92.4%
74.6%
33.9%
42.0%
47.0%
35.6%
0.57
0.73
0.81
0.57
68.2%
75.0%
73.0%
60.6%
0.55
0.64
0.67
0.59
28.0%
23.2%
22.8%
24.3%
63.6%
66.2%
69.1%
1.19
1.27
1.36
86.6%
92.5%
97.0%
31.2%
37.7%
47.8%
0.50
0.63
0.84
60.3%
68.5%
75.8%
0.49
0.57
0.69
32.4%
28.5%
21.2%
66.1%
1.24
87.3%
36.1%
0.60
65.5%
0.55
30.0%
72.8%
1.49
105.4%
39.4%
0.68
73.7%
0.54
33.4%
At provincial level, the screening coverage varied between 59.7% (W-Flanders) and
72.8% (Walloon-Brabant) for women with normal social status and between 31.2%
(Luxembourg) and 47.8% (Brussels) for women with special social status. The
geographical comparisons of the screening coverage between the two social
categories are potentially confounded, given the large variation in the proportion of
socially vulnerable categories by age. Therefore, age-standardised coverage rates
were computed, using the truncated European standard population as reference (19).
The results of this standardisation can be found in Table 19. Conclusions regarding
the standardised coverage rates are similar to those based on crude rates, given the
consistent lower coverage in women with special social status in all age groups. Agespecific contrasts are discussed further below.
In general, provinces with higher coverage among women without BIM status had
also higher coverage among women with BIR (Spearman’s correlation
coefficient=0.76; p=0.007).
The excess Pap smear use was significantly correlated with screening coverage in
both social groups (Pearson’s ρ=0.652 if BIR=0; ρ=0.627 if BIR=1). However, in a
linear regression describing the relation between coverage and excess use of Pap
smear (including BIR; age, region and province), the coefficient for the BIR covariate
was -0.08 (95% CI: -0.11 to -0.05), indicating that overscreening was significantly but
only slightly lower among socially vulnerable women).
Table 19. Age-standardised screening coverage (computed over the age range 25-64, using the
truncated European reference population) among women with and without BIR status. Ratio of
coverageBIR=1 / coverageBIR=0 and difference of coverageBIR=1 - coverageBIR=0
Belgium
BIR=0
54.3%
BIR=1
37.5%
Ratio
0.69
Difference
16.8%
Regions
Flemish Region
Brussels
Walloon Region
52.2%
59.4%
58.9%
32.8%
42.5%
41.0%
0.63
0.72
0.70
19.4%
16.8%
17.9%
Provinces
Antwerp
West-Flanders
East-Flanders
Hainaut
Liège
Limburg
Luxembourg
Namur
Brussels
Flemish-Brabant
Walloon-Brabant
52.9%
50.0%
51.6%
56.5%
61.5%
49.8%
54.8%
57.0%
59.4%
55.7%
64.1%
34.7%
31.0%
32.4%
40.6%
44.8%
30.8%
28.6%
36.8%
42.2%
32.3%
35.9%
0.66
0.62
0.63
0.72
0.73
0.62
0.52
0.65
0.71
0.58
0.56
18.2%
19.1%
19.1%
15.9%
16.7%
19.1%
26.1%
20.2%
17.2%
23.4%
28.2%
The variation in the screening coverage and the ratio # Pap smears/ # women by age,
computed over the period 2004-2006, for the two BIR groups, is shown in Figure 18,
for the whole of Belgium and, in Figure 20 and Figure 21, for each region and
province. The corresponding tables can be found in annex 12.5.
49
Belgium
BIR==0
BIR==1
1.4
1.2
1
.8
.6
.4
.2
0
15
25
35
45
55
65
75
15
25
35
45
55
65
75
Figure 18. 3-year screening coverage (red curve) and # Pap smears / # screened women (green curve)
ratio as a function of age (X axis), for women with normal social status (BIR=0, at left) and for women
with special social status (BIR=1, at right), for the whole of Belgium, 2004-06.
The corresponding tables can be found in annex 12.4 (Table 42-Table 44).
Figure 19 shows the curves of the screening coverage for both social categories in one
plot. The difference in coverage was low in the youngest groups (2% in the age group
15-19), increased by age (between 22% and 25%, in the age range 25-44) and then
decreased up to less than 10% for women of 70 and older).
80%
Screening coverage
70%
60%
50%
BIR=0
40%
BIR=1
30%
20%
10%
0%
15
25
35
45
55
65
75
Age group
Figure 19. 3-year screening coverage by age and by reimbursement status (BIR), Belgium, 2004-2006.
50
Flemish Region
BIR==0
BIR==1
1.4
1.2
1
.8
.6
.4
.2
0
15
25
35
45
55
65
75
15
25
35
45
55
65
75
35
45
55
65
75
35
45
55
65
75
Walloon Region
BIR==0
BIR==1
1.4
1.2
1
.8
.6
.4
.2
0
15
25
35
45
55
65
75
15
25
Brussels
BIR==0
BIR==1
1.4
1.2
1
.8
.6
.4
.2
0
15
25
35
45
55
65
75
15
25
Figure 20. 3-year screening coverage (red curve) and # Pap smears / # screened women ratio (green
curve) as a function of age (X axis), for women with normal social status (BIR=0, at left) and for
women with special social status (BIR=1, at right), for the three Belgian regions, 2004-2006.
51
Antwerp
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
35
45
55
65
75
35
45
55
65
75
35
45
55
65
75
35
45
55
65
75
West-Flanders
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
East-Flanders
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
Limburg
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
Figure 21a. 3-year screening coverage (red curve) and # Pap smears / # screened women ratio as a
function of age (X axis), for women with normal social status (BIR=0, at left) and for women with
special social status (BIR=1), for each province (2004-06).
52
Flemish-Brabant
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
35
45
55
65
75
35
45
55
65
75
35
45
55
65
75
35
45
55
65
75
Hainaut
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
Liège
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
Luxembourg
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
Figure 21b. 3-year screening coverage (red curve) and # Pap smears / # screened women ratio (green
women with special social status (BIR=1, at right), for each province (2004-06).
53
Namur
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
35
45
55
65
75
35
45
55
65
75
35
45
55
65
75
Walloon-Brabant
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
Brussels
BIR==0
BIR==1
1.6
1.2
.8
.4
0
15
25
35
45
55
65
75
15
25
Figure 21c. 3-year screening coverage (red curve) and # Pap smears / # screened women ratio (green
women with special social status (BIR=1, at right), for each province (2004-06).
54
7.3. Profession of Pap smear takers
There is a different code for smears taken by specialists and general practitioners. We
assumed that gynaecologists are the only specialists taking Pap smears.
Over the period 2002-06, 5.59 million records dealing with the collection of a cervical
Pap smear were notated, of which 0.59 million (10.6%) were taken by GPs and 4.99
million (89.4%) by gynaecologists. In the period 1996-2000, the number of Pap
smears taken by GPs was proportionally and in absolute numbers, substantially higher
(0.82 million smears, which was 15.5% of all Pap smears taken).
For 2002-06, we remark a difference of 0.83 million between the number of Pap
smears interpreted and taken. In the period 1996-2000, this difference was 0.48
million. It appears to happen that some Pap smears taken by gynaecologists are not
billed (Dr. G. Albertyn, personal communication, see reference (17)). If this
phenomenon is true the percentage of smears taken by gynaecologists could be higher.
Given the substantial differences between the regions we do not further detail the
statistics on Pap smear collection at the country level. Below, we present the
proportion of smears taken by GPs ignoring the gap of the 0.83 million Pap smears.
55
Important regional differences in the percentage of smears taken by GPs were
observed. Taking Pap smears remained an almost exclusive activity of gynaecologists
in the Walloon Region (>95 %). Moreover, this proportion had increased slightly
(from 96.2% in 1996-2000 versus 98.1% in 2002-06). In the Flemish Region, more
Pap smears were taken by GPs, but the proportion of all smears taken by GPs had
decreased with almost 5% (22.8% in 1996-2000 versus 16.1% in 2002-06).
In Brussels, 7% of Pap smears were prepared by GPs in the period 2002-06, which
was 2% less than in the 1996-2000. The trends in the proportion of Pap smears taken
by GP by calendar year and by region are shown in Figure 22 and in Table 20.
Flemish Region
Brussels
Fraction of smears taken by GPs
.3
.2
.1
0
2002
Walloon Region
2004
2006
.3
.2
.1
0
2002
2004
2006
Year
Figure 22. Trend in the proportion of Pap smears that is taken by GPs, by region (Belgium, 1996-2000
and 2002-2006).
Table 20. Proportion of Pap smears taken by GPs, by year and by region.
Year
1996
1997
1998
1999
2000
2002
2003
2004
2005
2006
56
Flemish Region
25.7%
24.7%
22.8%
21.5%
20.0%
18.0%
16.9%
16.1%
15.2%
13.9%
Brussels
10.2%
9.6%
9.0%
8.5%
8.3%
7.4%
7.0%
6.9%
6.8%
6.8%
Walloon Region
4.5%
4.2%
3.7%
3.6%
3.3%
2.2%
2.0%
1.8%
1.7%
1.6%
The proportion of smears taken by GPs varied by age (see Figure 23). The proportion
of GP smears showed a dip in the age groups where the coverage and intensity of
screening was highest.
Flemish Region
Brussels
.25
.2
.15
.1
.05
15
Walloon Region
25
35
45
55
65
75
.25
.2
.15
.1
.05
15
25
35
45
55
65
75
Age
Figure 23. Relation between the proportion of Pap smears taken by GPs and age group, by region
(Belgium, 2002-06).
The variation of the contribution of GPs in Pap smear taking over time and province is
shown in Figure 24. In 2006, the highest percentage of Pap smears taken by GPs was
highest in Limburg (18.0 %), Antwerp (17.2 %) and Flemish-Brabant (16.0%). The
decrease of the contribution of GPs over time was observed in all Flemish provinces.
In Liège and Hainaut only 1 over 100 of smears were prepared by GPs, in 2006 .
57
Antwerpen
Brussels
East-Flanders
Flemis h-Brabant
Hainaut
Limburg
Liège
Luxembourg
Namur
Walloon-Brabant
West-Flanders
.3
.2
.1
0
.3
.2
.1
0
1996
1999
2002
2005
.3
.2
.1
0
1996
1999
2002
2005
1996
1999
2002
2005
1996
1999
2002
2005
Year
Figure 24. Yearly trend in the proportion of cervical smears that are taken by GPs, by province.
The tables containing the proportion of Pap smears taken by GPs, repartitioned by
province and calendar year, can be found in annex 12.6.
58
7.4. Interval between successive Pap smears
The interval between successive Pap smear with the precision of one month concerns
women having at least two records for collection of cervical cells by a GP or a
specialist. In Table 21, distribution parameters (mean, quartiles and extremes) of the
testing intervals are given for all collections and by profession of the smear taker.
The average inter-testing interval was 15.3 months and the quartiles were
respectively: 11 (Q1), 13 (median) and 18 (Q3) months. When the smear was taken
by a GP compared to smears taken by a gynaecologist, the average inter-testing
interval was almost 2 months, and the median one month, longerh.
Table 21. Interval (in months) between successive Pap smear collections (Belgium, 2002-06), for all
Pap smears and by specialism of the physician taking the last smear.
Profession of smear
taker
All physicians
General practitioner
Gynaecologist
Minimum
0
0
0
25th
%ile
11
11
11
Median
13
14
13
75th
%ile
18
22
18
Mean
15.3
17.2
15.2
Maximum
59
59
59
The histogram with the overall distribution of the inter-testing intervals is shown, in
Figure 25, for all collections, and in Figure 26, separated by profession of the smear
taker. The modal interval was 12-15 months for both professional groups.
40
Percent
30
20
10
0
0
4
8
12
16
20
24 28 32 36
Interval (Months)
40
44
48
52
56
60
Figure 25. Distribution of the time interval between successive cytological examinations.
h
Without information on the result of the cytological examination, we cannot conclude with certainty
that the shorter interval between successive smears taken is an indicator of more over-screening by
gynaecologists compared to GPs
59
Pap smears taken by general practioners
40
30
30
Percent
Percent
Pap smears taken by gynaecologists
40
20
10
20
10
0
0
0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60
Interval (Months)
0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60
Interval (Months)
Figure 26. Distribution of the time interval between successive cytological examinations, according to
the profession of the physician taking the last Pap smear.
Figure 27 shows the variation of the average interval by age group. There was an
increase by age noted in the three youngest categories (<25 years). However, it
should be noted that the number of records in the youngest group (10-14 years) was
very small (N=131). After the age of 25, the average interval remained rather
constant at 15 months.
Intertesting interval (months)
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
10
20
30
40
50
60
70
Age group
Figure 27. Average interval between successive Pap smear collections according to age group
(labelled by the first year of the five-year age group).
The other distribution parameters (extremes and quartiles) for each age group and also
for each province can be found in annex 12.7 (respectively Table 51 and Table 52).
The variation of the inter-test interval was also assessed using a multivariate linear
regression model, including the following covariates: profession of the smear taker,
social status, age and residence (province) of the woman (see
Table 22). The interval did not vary by the woman’s social status but varied
significantly by age and by the profession of the smear taker. In most provinces, the
interval was slightly shorter than in Antwerp (reference), with the exception of
Limburg and Luxembourg where it was slightly longer.
60
Table 22. Differences in interval between successive Pap smears compared to the average=16.1
months for the reference category: last smear taken by a GP in a woman from Antwerp of age 20-24
years. Estimates in months computed by multivariate linear regression.
Change in
interval
(months)
95% CI
Profession of physician taking last Pap smear: ref=GP
Gynaecologist
-1.9 (-1.9 to -1.8)
Social category: ref=normal status
Special status
0.0
(-0.1 to 0)
Age group: ref= 20-24 years
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
>= 75
0.6
0.8
0.9
0.9
0.8
0.6
0.6
0.8
0.7
0.7
0.9
(0.5 to 0.6)
(0.8 to 0.9)
(0.9 to 0.9)
(0.9 to 1.0)
(0.8 to 0.9)
(0.5 to 0.6)
(0.6 to 0.7)
(0.8 to 0.9)
(0.6 to 0.8)
(0.6 to 0.8)
(0.8 to 1.0)
-0.2
-0.7
-0.4
-0.2
0.4
0.2
-0.2
-1.4
-0.3
-1.0
(-0.2 to -0.2)
(-0.7 to -0.7)
(-0.4 to -0.3)
(-0.2 to -0.1)
(0.4 to 0.5)
(0.1 to 0.2)
(-0.3 to -0.2)
(-1.5 to -1.4)
(-0.4 to -0.3)
(-1.1 to -1)
Province: ref=Antwerp
W-Flanders
E-Flanders
Hainaut
Liège
Limburg
Luxembourg
Namur
Brussels
Fl-Brabant
Wal-Brabant
Table 23 shows the repartition of the time between successive smears aggregated by
multiples of 12 months and for different geographical levels. The same type of
repartition by age group is shown in Table 24. The interval of 36 months or more was
notated in only 3% of women with two or more Pap smears. This proportion varied
only slightly by geographical level and by age group.
The proportion of successive Pap smears with an interval of less than 12 months (an
indicator of over-screening) was 30%, varying between 28% (Flemish Region) and
36% (Brussels) at the regional level, and between 26% (Luxembourg) and 36%
(Brussels) at the provincial level. The proportion was positively correlated with the
excess smear use (correlation coefficient [ρ] = 0.59) and with screening coverage (ρ
=0.49).
The proportion decreased by age: from 42% in age group 15-19 to 25% in age group
60-66, with a slight increase for women of 65 years or older.
61
Table 23. Time between successive Pap smears, by geographical level.
Area
Belgium
<12M
29.5%
12-23M
56.1%
24-35M
11.0%
36-59M
3.4%
Region
Flemish Region
Brussels
Walloon Region
28.1%
35.8%
29.4%
56.5%
52.1%
56.9%
11.6%
9.4%
10.6%
3.8%
2.7%
3.1%
Province
Censored
Unknown
Antwerp
West-Flanders
East-Flanders
Hainaut
Liège
Limburg
Luxembourg
Namur
Brussels
Flemish-Brabant
Walloon-Brabant
45.6%
35.8%
27.9%
28.5%
29.0%
30.3%
28.4%
26.7%
25.5%
29.3%
35.8%
28.0%
31.2%
41.2%
52.8%
55.8%
56.7%
57.5%
55.9%
57.6%
55.1%
60.4%
56.3%
52.1%
57.1%
57.6%
9.5%
8.8%
12.1%
11.3%
10.4%
10.6%
11.0%
13.7%
11.0%
11.1%
9.4%
11.4%
8.9%
3.7%
2.7%
4.2%
3.6%
3.1%
3.3%
3.1%
4.5%
3.2%
3.3%
2.7%
3.5%
2.3%
Table 24. Time between successive Pap smears, by age group.
Age group
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
62
<12M
42.4%
35.2%
34.2%
32.1%
29.7%
28.0%
27.8%
27.6%
26.0%
24.8%
25.2%
26.5%
29.6%
12-23M
50.6%
52.0%
51.3%
52.9%
55.3%
57.0%
57.7%
59.0%
60.5%
60.6%
60.4%
58.6%
54.2%
24-35M
6.0%
9.9%
11.1%
11.4%
11.3%
11.4%
11.0%
10.4%
10.4%
11.1%
11.2%
11.6%
12.0%
36-59M
1.0%
2.9%
3.5%
3.6%
3.6%
3.7%
3.5%
3.1%
3.1%
3.5%
3.2%
3.3%
4.2%
7.5. Colposcopies & cervical biopsies
About 400.000 colposcopic examinations were performed each year in Belgium. The
time, age and geographical distribution of the number of colposcopies, cervical
biopsies and interpretations of Pap smears and the ratios of these numbers are
documented in Table 25-28.
The average number of Pap smears interpreted per colposcopy was 3.2 in 2002-06.
This ratio increased slightly over time from 2.8 in 1996 to 3.4 in 2006. The variation
of this ratio by age was limited but substantial by region and by province. In the
Walloon Region this ratio was only 1.7, whereas it was 3.0 in the Brussels-Capital
Region and 7.8 in the Flemish Region. The regional contrast had increased over time:
in 1996-2000, it was 1.8 in the Walloon Region, 2.8 in the Brussels-Capital Region
and 4.9 in the Flemish Region.
At provincial level the variation in the Pap/colposcopy ratio was larger: from 1.6 in
Hainaut and Liège, to 11.4 in West-Flanders.
Table 25. Number of colposcopies, cervical biopsies taken and Pap smears interpreted, ratio of the
number of biopsies over the number of colposcopies, ratio of the number of Pap smears over the
number of colposcopies and ratio of the number of biopsies over the number of Pap smears, Belgium,
by year, in the periods 1996-2000 and 2002-2006.
Year
1996
1997
1998
1999
2000
1996-00
2002
2003
2004
2005
2006
2002-06
Colposcopies
378,750
398,704
408,634
410,083
413,785
2,009,956
395,598
396,828
401,457
403,370
383,674
1,980,927
Biopsies
22,063
20,143
22,048
21,108
20,776
106,138
17,967
18,885
18,261
19,451
19,209
93,773
Pap
Biopsy/colposcopy Pap/colposcopy Biopsy/Pap
smears
ratio
ratio
ratio
1,042,821
5.8%
2.8
2.1%
1,095,337
5.1%
2.7
1.8%
1,171,347
5.4%
2.9
1.9%
1,201,152
5.1%
2.9
1.8%
1,223,544
5.0%
3.0
1.7%
5,734,201
5.3%
2.9
1.9%
1,258,881
4.5%
3.2
1.4%
1,270,521
4.8%
3.2
1.5%
1,294,178
4.5%
3.2
1.4%
1,299,050
4.8%
3.2
1.5%
1,295,306
5.0%
3.4
1.5%
6,417,936
4.7%
3.2
1.5%
63
Table 26. See Table 25, Belgium 2002-2006, by age group.
Age
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
>= 75
Total
Colposcopies
1,633
50,708
156,986
224,472
248,981
242,127
234,584
218,707
192,815
153,399
96,832
74,877
47,793
37,013
1,980,927
Biopsies
65
1,794
8,402
12,982
13,932
13,209
12,001
9,870
7,152
4,786
3,201
2,652
1,903
1,824
93,773
Pap
smears
2,919
146,708
498,375
704,465
790,455
810,657
801,194
727,865
623,750
495,633
322,477
236,194
147,013
110,231
6,417,936
Biopsy/
colposcopy ratio
4.0%
3.5%
5.4%
5.8%
5.6%
5.5%
5.1%
4.5%
3.7%
3.1%
3.3%
3.5%
4.0%
4.9%
4.7%
Pap/
colposcopy
ratio
1.8
2.9
3.2
3.1
3.2
3.3
3.4
3.3
3.2
3.2
3.3
3.2
3.1
3.0
3.2
Biopsy/Pap
ratio
2.2%
1.2%
1.7%
1.8%
1.8%
1.6%
1.5%
1.4%
1.1%
1.0%
1.0%
1.1%
1.3%
1.7%
1.5%
On average, 4.7% of the colposcopies were accompanied by taking a cervical biopsy.
Again this percentage varied slightly by age and time. This percentage was 2.4%,
5.4% and 11.0% in the Walloon, Brussels-Capital and Flemish Region, repectively. It
was highest in Antwerp (16.3%) and lowest in Liège (2.0%).
On average the ratio of the number of cervical biopsies over the number of Pap
smears was 1.5%. The variation of biopsy/pap smear ratio by age is displayed in
Figure 28. This ratio varied only slightly by region, indicating minor inter-regional
differences in prevalence of colposcopically visible cervical lesions that resulted in a
biopsy. The range of variation at provincial level was rather small as well, with most
provinces in the range of 1.2-1.6%, with exception of West-Flanders (0.8%) and
Antwerp (1.6%).
Table 27. See Table 25, Belgium, 2002-2006, by region.
Region
Colposcopies
Biopsies Pap smears
Undefined
18199
2100
53298
Flemish Region
441,027
48,559 3,456,854
Brussels
229,164
12,460
677,749
Walloon Region
1,292,537
30,654 2,230,035
Total
1,980,927
93,773 6,417,936
64
ratio
ratio
ratio
11.5%
2.9
3.9%
11.0%
7.8
1.4%
5.4%
3.0
1.8%
2.4%
1.7
1.4%
4.7%
3.2
1.5%
Table 28. See Table 25, Belgium 2002-2006, by province.
Biopsy / Pap smear ratio
Province
Colposcopies
Biopsies Pap smears
Censored
9975
1788
33213
Unknown
8224
312
20085
Antwerp
103270
16848
959181
West-Flanders
53152
5016
606616
East-Flanders
102497
13367
817384
Hainaut
509706
11578
814604
Liège
454224
9228
714337
Limburg
64502
5432
415439
Luxembourg
72844
1696
124688
Namur
131382
4199
290803
Brussels
229164
12460
677749
Flemish-Brabant
117606
7896
658234
Walloon-Brabant
124381
3953
285603
ratio
ratio
ratio
17.9%
3.3
5.4%
3.8%
2.4
1.6%
16.3%
9.3
1.8%
9.4%
11.4
0.8%
13.0%
8.0
1.6%
2.3%
1.6
1.4%
2.0%
1.6
1.3%
8.4%
6.4
1.3%
2.3%
1.7
1.4%
3.2%
2.2
1.4%
5.4%
3.0
1.8%
6.7%
5.6
1.2%
3.2%
2.3
1.4%
2.0%
1.8%
1.6%
1.4%
1.2%
1.0%
0.8%
0.6%
0.4%
0.2%
0.0%
15 20 25 30 35 40 45 50 55 60 65 70 75
Age group
Figure 28. Ratio of the number of cervical biopsies over the number of Pap smears taken, by age
(Belgium, 2002-2006).
65
7.6. Hysterectomies
7.6.1. National level
In total, 83,542 total hysterectomies were performed in Belgium between 2002 and
2006 (Table 29). The number of hysterectomies by year decreased from 17,700 to
15,706, which corresponds with an average annual change of –431/year (=slope of
linear regression).
Table 29. The total number of total hysterectomies performed, each year, in Belgium in the period
2002-2006.
Year
2002
2003
2004
2005
2006
Total
Frequency
17,700
16,785
16,897
16,454
15,706
83,542
Percent
21.2
20.1
20.2
19.7
18.8
100.0
The average yearly incidence rate of total hysterectomy per thousand women and by
age, computed over the period 2002 to 2006, is plotted in Figure 29. The resulting
cumulative incidence (which is nearly equivalent to the prevalence of being totally
hysterectomisedi) by age is shown in Figure 30.
The overall incidence within the 25-64 years group was 4.8 per 1000 women-years.
The age-specific incidence rate increased up to a peak at 9.2/1000 women-years in the
50-54 year age group. The hysterectomy rate declined thereafter to reach a rather
constant level between 4.0 and 4.2 per 1000/year in the age groups 55-74. The
increase in the last age group (women of 75 years or older) might be due to the
assumption that all hysterectomies in the age group 75+ were considered to occur all
within the age group 75-79.
Figure 31 shows the observed incidence rate of hysterectomy among women of 25-64
years old and also the linear trend obtained from a Poisson regression using the
calendar year as a continuous covariate. The linear trend was mildly decreasing
(slope: 0.971; 95% CI: 0. .966 to 0. 976).
Figure 32 displays the time trend of the observed hysterectomy incidence rate for 3
separate age groups. The rate was mildly decreasing in the youngest age group (<45
years old women: slope of 0.978 [95% CI: 0.970-0.987]). The decreasing trend was
more pronounced in the two older age groups: (0.960 [95% CI: 0.954-0.967]) in age
group 45-64 and 0.959 [95% CI: 0.949-0.969]) in women of 65 and older.
Figure 33 shows the trends over 11 years (1996-2006).
i
Under the assumption of absent period effect.
66
Hysterectomies/1000 women-years
10
7.5
5
2.5
0
20
30
40
50
Age group
60
70
Figure 29. Average incidence of total hystectomy by age (Belgium, 2002-2006).
Cumulative incidence (%)
25
20
15
10
5
0
20
30
40
50
Age group
60
70
Figure 30. Average cumulative incidence of hysterectomy, up to a given age group (Belgium, 20022006).
67
6
5
4
3
2
1
0
2002
2003
2004
Year
2005
2006
Figure 31. Observed incidence rates of hysterectomy (red circles) and fitted linear trend between 2002
and 2006 among women between 25 and 64 years old.
15-44 years
>=65 years
45-64 years
8
6
4
2
0
2002
2003
2004
Year
2005
2006
Figure 32. Observed trend of hysterectomy rates by age group in Belgium between 2002 and 2006.
68
6
5
4
3
2
1
0
1996
1998
2000
Year
2002
2004
2006
Figure 33. Observed incidence rates of hysterectomy (red circles) and linear trend between 1996 and
2006 among women between 25 and 64 years old.
69
The average age-specific incidence of hysterectomy is shown for the three regions
separately in Figure 34. The shape of the curve was similar for the three regions as
described for the whole of Belgium in the previous subchapter. However the age
specific incidences were substantially higher in the Flemish and substantially lower in
the Brussels-Capital Region. Peak incidences occurred systematically in the 45-49
year age group: respectively 6.9, 5.4 and 6.5 per 1000 women-years in the Flemish,
Brussels-Capital and Walloon Region.
Flemish Region
Brussels
8
6
4
2
0
25
Walloon Region
40
55
70
8
6
4
2
0
25
40
55
70
Age group
Figure 34. Average incidence of total hystectomy by age (Belgium, by region, 2002-2006).
The cumulative incidence of hysterectomy up to a given age is plotted in Figure 35.
Figure 36 shows the observed incidence rate of hysterectomy among women of 25-64
years old and also the linear trend obtained from a Poisson regression. This Poisson
regression included an interaction between region and year, expressed as a continuous
variable. The decreasing trend was largest in the Flemish Region, smaller in the
Walloon Region, and non significant in the Brussels-Capital Region: linear slopes of
0.977 (95% CI: 0.871 to 0.984); 0.986 (95% CI: 0.974 to 0.998) and 0.984 (95% CI:
0.962 to 1.01), respectively.
The time trend over the 5 calendar years for 3 separate age-groups is shown in Figure
37. In general, trends were nearly linear. In the Brussels-Capital Region, the trend
decreased until 2004 in women of 45 and older but did not further drop thereafter.
70
Cumulative incidence of hysterectomy up to a given age group
Cumulative incidence (%)
Flemish Region
Brussels
30
25
20
15
10
5
0
20
Walloon Region
30
40
50
60
70
30
25
20
15
10
5
0
20
30
40
50
60
70
Age group
Figure 35. Average cumulative incidence of hysterectomy, up to a given age group (Belgium by
region, 2002-2006).
Flemish Region
Brussels
6
5
4
3
2
1
0
2002
Walloon Region
2003
2004
2005 2006
6
5
4
3
2
1
0
2002
2003
2004
2005 2006
Year
Figure 36. Observed incidence rates of hysterectomy (red circles) and linear trend, by region, between
2002 and 2006 among women between 25 and 64 years old.
71
15-44 years
>=65 years
45-64 years
Flemish Region
Brussels
8
6
4
2
0
2002
Walloon Region
2003
2004
2005 2006
8
6
4
2
0
2002
2003
2004
2005 2006
Year
Figure 37. Observed trend of hysterectomy rates by age group in the three Belgian regions between
2002 and 2006.
72
For the provinces, we just present the average yearly incidence, which is plotted as a
function of age in Figure 38. Remark the higher incidences (peak incidence at 45-49
year > 9/1000 women years) in the provinces of Antwerp (9.7), West-Flanders (9.5),
East-Flanders (10.3) and Limburg (9.2).
Antwerpen
West-Flanders
East-Flanders
Hainaut
Liège
Lim burg
Luxem bourg
Nam ur
Brussels
10
5
0
10
5
0
10
5
0
25 40 55 70
25 40 55 70
Flemish-Brabant
Walloon-Brabant
25 40 55 70
15
10
5
0
25
40
55
70
25
40
55
70
Figure 38. Average incidence of total hysterectomy by age (Belgium, by province, 2002-2006).
73
7.7. Cytological screening in hysterectomised women
Women who have undergone total hysterectomy are not at risk for cervical cancer if
the indication for the intervention was not oncologic. In the next subchapter we will
study the intensity of Pap smear use in women who had total hysterectomy or cervixamputation in the studied period. Since we do not know if smears taken in the same
calendar year as the hysterectomy, took place before or after the surgery, we will
consider the calendar years after the hysterectomy. Two types of post-hysterectomy
periods are defined: one-year (see subchapter 7.7.1) and three-year periods (see
subchapter 7.7.2).
7.7.1. Use of Pap smears one year after hysterectomy
The proportion of women with a hysterectomy in a given year in the period 20022006 and who had a least one Pap smear in the subsequent year, specified by age
group, is shown in Figure 39. No time trend effects could be discerned, since the
curves for the four years coincide. The proportion of screened women was highest
among young women: on average 69% among 20-29 years old women. This
percentage decreased with age, to reach the lowest level in the age groups 40-54 (on
average 15%). The proportion increased a few percentages in the age group 55-64 (on
average 21%) and it decreased again until 15% in women being 70 or older.
The ratio of the number of smears taken over the number hysterectomised women is
plotted in Figure 40.
Table 30 shows by five-year groups the number of hysterectomies performed in 2005
and the number of Pap smears examined among the hysterectomised women in 2006.
It shows also the proportion of screened hysterectomised women and the #smears/
#women ratio which corresponds to the blue curves in Figure 39 and Figure 40. Both
measures are plotted in one graph (see Figure 41). The number of smears per
screened hysterectomised woman varied between 1.3 (in age group 50-54) and 1.7 (in
age group 20-24 year age group).
Among the 16,231 women hysterectomised in 2005; 3,070 were screened
cytologically using on average 1.4 Pap smears per screened woman during the year
2006.
74
Pap smears in women being hysterectomised 1 year before
#smear / #women ratio; by year of hysterectomy and age
2002
2004
2003
2005
#smears / #hectomised women
1.2
1
.8
.6
.4
.2
0
25
35
45
Age group
55
65
Figure 39. Proportion of women with hysterectomy occurring in the year indicated in the legend, who
had at least one Pap smear in the subsequent year.
Table 30. Cytological screening in 2006 among women who underwent a total hysterectomy in 2005.
Number
of
Age
20
25
30
35
40
45
50
55
60
65
70
75+
25-64
20+
Women with
Proportion of
#smears/
#smears/
smear in
women with smear #women ratio #screened women
in 2006
1.71
65
82.3%
1.41
155
1.60
64.9%
1.04
246
1.52
41.8%
0.64
325
1.46
24.5%
0.36
449
1.36
15.8%
0.22
491
1.30
14.0%
0.18
325
1.29
15.6%
0.20
255
1.45
20.1%
0.29
221
1.55
23.2%
0.36
193
1.57
18.5%
0.29
170
1.51
17.5%
0.26
175
1.57
13.0%
0.21
1.41
19.3%
0.27
3,475
2,467
1.44
18.9%
0.27
4,420
3,070
Hysterectomies Smears
in 2005
in 2006
79
111
239
248
588
375
1,326
473
2,836
612
3,504
637
2,081
418
1,268
370
953
342
1,042
303
974
256
1,341
275
12,795
16,231
75
Pap smears in women being hysterectomised 1 year before
#smear / #women ratio; by year of hysterectomy and age
2002
2004
2003
2005
1.2
1
.8
.6
.4
.2
0
25
35
45
Age group
55
65
Figure 40. Use of Pap smears in hysterectomised women: ratio of # smears/ # women, where # smears
is the number of Pap smears taken in the calendar-year following the year where hysterectomy took
place and # women is the number of women who underwent a total hysterectomy in the year defined in
the legend.
Pap smears taken in 2006 in women being hysterectomised in 2005
#smears/#women ratio
proportion with at >=1 smear
1
.5
0
25
35
45
Age group
55
65
Figure 41. Pap smear use in hysterectomised women. Red full line curve: proportion of women with
hysterectomy in 2005 who had at least one Pap smear in 2006; Green interrupted line curve: ratio of the
number of Pap smears taken in 2006/ number of women hysterectomised in 2005.
76
7.7.2. Use of Pap smears in the 3-year period following
hysterectomy
The proportion of hysterectomised women who had a Pap smear taken in the three
subsequent years is plotted using a full line curve in Figure 42. The #smears/#women
ratio is plotted on the same graph using interrupted lines. These indicators are
documented for two hysterectomy years: 2002 and 2003. Absolute values and
computed indicators are enumerated in Table 31. The proportion of screened women
was highest in the youngest groups (76% in the 20-29 year age group) and it
decreased until 20% in the 45-49 year group. This proportion increased until 26% in
the 55-64 year group and finally decreased again (18% in women of 70 years and
older). The number of smears per screened women was on average 2.4 and varied
between 2.1 and 3.1 by age group.
#women/#smears ratio
Proportion w Pap, Hectomy 2002
#women/#smears ratio
Proportion w Pap, Hectomy 2003
2.5
2
1.5
1
.5
0
25
35
45
Age group
55
65
Figure 42. Pap smear use in hysterectomised women. Full line curves: proportion of women with at
least one smear in the 3-year period following the year of hysterectomy; interrupted line curves: #
smears taken in the three subsequent years/ # women hysterectomised in a given year; red line curves:
concerning women hysterectomised in 2002; blue line curves: concerning women hysterectomised in
2003.
77
Table 31. Cytological screening in 2004-2006 among women who underwent a total hysterectomy in
2003.
Age
20
25
30
35
40
45
50
55
60
65
70
75
# smears/#screened
Women with Proportion of women
#smears/
women
Hysterectomies
Smears
smear
with smear
#women ratio
in 2003
in 2004-2006 in 2004-2006
2.85
70
157
55
78.6%
2.24
3.08
210
487
158
75.2%
2.32
2.98
633
954
320
50.6%
1.51
2.54
1,450
1,127
443
30.6%
0.78
2.22
2,922
1,579
712
24.4%
0.54
2.06
3,337
1,359
659
19.7%
0.41
2.19
2,205
1,113
508
23.0%
0.50
2.28
1,344
788
346
25.7%
0.59
2.48
1,031
666
269
26.1%
0.65
2.66
1,115
736
277
24.8%
0.66
2.28
1038
523
229
22.1%
0.50
2.21
1262
416
188
14.9%
0.33
25-64
13,132
8,073
3,415
26.0%
0.61
20+
16,617
9,905
4,164
25.1%
0.60
78
2.36
2.38
8. Discussion
8.1. Quality of the dataset
The quality of the dataset was compromised by truncating details of information such
as date of the act, age of the women, locality of residence. However, in the current
report, contrary to the previous one, we were able to evaluate the interval between the
successively collected Pap smears with more detail (months instead of years). For
other acts only the year was provided. Because more time detail regarding the
collection of Pap smears was given, less geographical information regarding the
residence of the women (only province instead of district) was provided. This lack of
geographical detail impeded us to produce district choropleth maps as in the previous
report (17).
The identities of the respective women were irreversibly encrypted. Nevertheless
records can refer to a unique person by their content when locality, age and date of the
medical act are known. Truncation of data was done to reduce the probability of
providing unique data, which theoretically include a risk of identifiability.
Nevertheless, one should not confound uniqueness with identifiability.
The amount of records with improbable results (women with multiple hysterectomies,
or with more then 20 smears in five years) was limited (<1% of the complete dataset).
8.2. Comparison with results of the National Health Interview
Survey (HIS)
In 2001 and 2004, a nation-wide health interview surveys (HIS) was conducted
including respectively 10,000 and 12,000 households, randomly chosen from the
national register using a stratified cluster sampling design (15). The questionnaire
contained seven questions on cervical cancer screening by Pap smear, which were
addressed to all selected women older than 14 years. The following questions were of
interest for this report: “Did you ever had a gynaecological examination for cervical
cancer (a cervical smear); b) If yes, how long ago did this happen? (<1 year ago; 1-3
years ago, 3-5 years ago; more than 5 years ago, no answer). From the answers to
these two questions an indicator variable for 3-year screening coverage was
constructed (having had a Pap smear taken less then 3 years ago). Another question
of interest was: “Did you ever undergo a cervical ablation of the cervix?”
We applied the same statistical weighting procedures as described by the authors of
the HIS report (15).
Table 32 shows the coverage estimated from the health interview surveys in 2001 and
2004 confronted with the coverage computed from the individual health insurance
data set for respectively one year later and before at the level of Belgium and the three
regions for women in the target age range of 25-64 years. The coverage, estimated
from HIS data, was substantially and statistically significantly higher than in our
study. At the national level this difference was 11.5% (CI: 9.3-13.6%). The
79
difference between 2001 (HIS-data) and the 2000 coverage (IMA-AIM) was highest
in the Flemish and the Brussels-Capital Region, respectively 12.1% (CI: 8.8-15.1%)
and 11.7% (CI: 7.9-15.2%). In the Walloon Region, this difference was slightly
smaller (10.5%; CI: 7.0-16.8%).
Table 32. Comparison of the 3-year cervical cancer screening coverage estimated from the health
interview surveys conducted in 2001 and 2004 and the coverage computed from individual health
insurance data form the periods 1998-2000 and 2002-2004, among women between 25 and 64 years
old, in Belgium and by region.
Health Interview Survey (HIS)
Year
Belgium
Flemish Region
Capital Region
Walloon Region
2001
Estimate (95% CI)
69.9% (67.9% -72.5%)
2004
Estimate
(95% CI)
72.2% (70.0% -74.3%)
71.9% (68.7% -74.9%)
72.4% (68.6% -75.9%)
65.6% (61.4% -69.7%)
71.3% (68.0% -74.3%)
74.0% (70.2% -77.5%)
73.4% (69.8% -76.6%)
Individual patient
files from IMA-AIM
2000
2004
Coverage
58.6%
60.7%
57.4%
57.6%
60.9%
59.2%
62.3%
62.8%
Table 33 shows values of coverage at the provincial level estimated from the 2004
health survey or computed for the same year from the individual health insurance
data. The HIS-coverage was always higher and the difference was always statistically
except for Flemish- and Walloon-Brabant.
Table 33. Comparison of the 3-year cervical cancer screening coverage estimated from the health
interview survey (HIS, 2004) and the coverage computed from individual health insurance data for the
year 2000, among women between 25 and 64 years old, by province.
Province
HIS, 2004
Antwerp
73.3%
Flemish-Brabant
78.0%
West-Flanders
69.0%
East-Flanders
66.2%
Limburg
71.0%
Brussels
74.0%
Walloon-Brabant
77.0%
Hainaut
66.9%
Liège
79.0%
Luxembourg
76.5%
Namur
74.3%
80
(95% CI)
(66.9%-78.8%)
(61.4%-75.8%)
(59.0%-72.8%)
(64.1%-77.0%)
(70.2%-77.5%)
(67.2%-84.6%)
(60.4%-72.9%)
(72.9%-84.0%)
(70.7%-81.5%)
(63.9%-82.5%)
(70.0%-74.3%)
Individual patient files
from IMA-AIM (200204)
60.5%
63.1%
56.6%
58.9%
55.9%
62.3%
70.0%
61.1%
65.4%
50.9%
62.6%
Table 34 and Figure 43 show the same type of contrast at the Belgian level but now
differentiated by age group.
Table 34. Estimation of the 3-year cervical cancer screening coverage estimated from the national
health interview survey (HIS) in 2004 and the corresponding coverage computed from individual
health insurance data (provided by IMA-AIM) for the period 2002-04, Belgium, by age group.
HIS, 2004
Age group
Estimate
15-19
15.3%
20-24
49.9%
25-29
74.8%
30-34
80.3%
35-39
73.8%
40-44
73.7%
45-49
74.3%
50-54
68.0%
55-59
71.2%
60-64
54.9%
65-69
39.7%
70-74
30.3%
75+
13.9%
(95% CI)
(9.7% -23.2%)
(41.7% -58.1%)
(68.6% -80.1%)
(74.2% -85.3%)
(67.4% -79.3%)
(67.6% -79.0%)
(68.0% -79.8%)
(61.0% -74.2%)
(65.0% -76.7%)
(47.2% -62.4%)
(33.3% -46.5%)
(24.3% -37.0%)
(10.4% -18.3%)
IMA-AIM,
2002-04
Coverage
16.8%
51.2%
67.9%
69.7%
65.8%
64.5%
61.4%
56.4%
51.2%
40.8%
30.5%
19.9%
18.7%
In the age groups 25-74, the coverage estimated from the HIS data was significantly
higher than that computed from the IMA-AIM data, and this difference tended to
increase with age up to the age group of 55-59.
Substantial discrepancies in coverage derived from two independent data sources are
observed. We assume that the coverage computed from the individual health
insurance data has a higher likelihood to correspond more to the true coverage since it
does not suffer from reporting and selection biases inherent to health interview
surveys, and is only influenced by “minor” administrative errors [R. Mertens; V.
Fabri: personal communications]. Several authors, who investigated the accuracy of
self-reported utilisation of Pap smears found systematic overestimation of the actual
screening status (20-27). Selective participation of screened women in surveys is
another explanation (11,14). Finally, another potential reason of overestimation might
be due to the fact that 11% of women in the age range 25 64 year did not answer the
question “Have you ever had a Pap smear taken” and probably the screening status in
this category was lower than among responding women.
The overestimation of the screening coverage was general in all regions (range:10.5%12.1%) and provinces (5.9%-25.7%).
The question whether the woman had undergone a total hysterectomy was not
included any more in the HIS of 2004. The proportion of women, being 25 to 64 year
old, that declared having undergone hysterectomy, could be estimated from the health
interview survey in 2001. The estimated proportion was 9.9% (CI: 8.8%-11.0%).
81
The prevalence of total hysterectomy, derived from the cumulative incidence in the
individual health insurance data file (described in a previous report) was 8.9%
(16,17). Both figures approximate each other remarkably well. Answers to the
hysterectomy question were probably more accurate than those concerning cervical
screening.
Memory and projection biases are probably negligible, since a
hysterectomy is a drastic intervention in a woman’s life.
8.3. Comparison with statistics from the National Institute for
Health and Disability Insurance
The National Institute for Health and Disability Insurance (NIHDI) produces yearly
statistics for each code from the list of medical acts. These reports do not contain
details of age or place of the patient and are only based on bookkeeping dataj.
8.3.1. Collection and interpretation of cervical smears
Figure 44 shows the trend in the number of interpreted smears by year between 1983
and 2009. Between 1994 and 2008 (excluding 1983, which might be incomplete) the
annual number of Pap smear interpretations increased from about 0.6 million to
almost 1.4 million. Also the NIHDI expenses for interpretation and for the sum
interpretation + collection, expressed in EURO or EURO-equivalentsk, are plotted.
The financial resources spent in 2008 by the health authority to reimburse cervical
examinations was around 28 million EURO (costs for medical visits not included).
An important trend break was noted in 2009 due to a change in the reimbursement
rules introduced on 1/07/2009. Since then, a cervical cytological examination for
reasons of screening is reimbursed only once every 24 months (without age
restriction), whereas a follow-up Pap smear within 6 months is only reimbursed when
it follows a previous cytological abnormality. In 2009, the total number of examined
Pap smears was 1.15 million, more than 200,000 less than in 2008.
In Table 35, the numbers of smears, collected by GPs or by specialists and interpreted,
reported by the NIHDI are compared with those computed from the individual patient
data set. Again we observed that the sum of the number of smears taken was higher
than the number of smears interpreted.
Moreover, important absolute and
proportional differences were observed between the two databases. The number of
interpreted smears was substantially higher in the NIHDI database in 1996 and 1997.
In the subsequent years the difference was less than 1.5%.
j
According to the NIHDI’s bookkeeping system, a year spans the months January-October of the
current year and November-December of the passed year. In 1996 more files were processed due to a
delay in bookkeeping in 1995. The difference between IMA-AIM’s data and NIHDI’s data can be
explained by the source of the data. IMA-AIM’s data are registered the day the medical act is realised.
NIHDI’s data are based on bookkeeping data that record the date of the reimbursement of the medical
act.
k
Expenses before 2002 where in Belgian francs and had to be recalculated into EURO by dividing the
amount in Belgian francs by 40.3399 to give the resulting amount in EUROs.
82
Differences between the two databases were expected because statistical information
from the NIHDI is based on bookkeeping data, where the invoice date is considered.
Furthermore, according to the NIHDI’s bookkeeping system, a year spans the months
January-October of the current year and November-December of the passed year. In
1996 more files were processed due to a delay in bookkeeping in 1995, which
explains the positive differences between NIHDI and IMA-AIM.
Table 35. Number of smears collected by GPs, specialists and number of smears interpreted by year in
Belgium, as reported in the yearly statistics of the National Institute for Health and Disability Insurance
(NIHDI) and as computed from the individual patient data provided by IMA-AIM. Absolute and
relative differences between both databases.
Proportional difference
NIHDI
Collection Pap by
Year
GP
Difference (NIHDI-IMAAIM)
IMA-AIM
Inter-
specialist pretation
Collection Pap by
GP
Inter-
Collection Pap by
GP
(NIHDI-IMA-AIM)/NIHDI]
Inter-
Collection Pap by
7,560
GP
Inter-
1996
173,265
813,131 1,199,523
165,705
775,255 1,042,821
37,876
156,702
4.4%
4.7%
13.1%
1997
167,323
825,610 1,167,172
169,945
839,161 1,095,337 -2,622 -13,551
71,835
-1.6%
-1.6%
6.2%
1998
161,218
867,308 1,176,029
167,574
909,139 1,171,347 -6,356 -41,831
4,682
-3.9%
-4.8%
0.4%
1999
152,362
891,876 1,207,414
160,524
942,069 1,201,152 -8,162 -50,193
6,262
-5.4%
-5.6%
0.5%
2000
142,828
911,903 1,219,127
152,034
969,792 1,223,544 -9,206 -57,889
-0.4%
2001
142,279
955,612 1,289,337
-
2002
131,255
957,667 1,251,716
2003
124,653
980,774 1,257,213
2004
121,380 1,013,789 1,313,169
2005
114,544 1,020,123 1,303,014
113,963 1,019,551 1,299,050
581
2006
111,427 1,034,878 1,284,425
109,056 1,025,553 1,295,306
2,371
-4,417
-6.4%
-6.3%
-
-
-
-
-
-
-
129,001
960,424 1,258,881
2,254
-2,757
-7,165
1.7%
-0.3%
-0.6%
122,714
982,089 1,270,521
1,939
-1,315
-13,308
1.6%
-0.1%
-1.1%
119,146 1,003,796 1,294,178
2,234
9,993
18,991
1.8%
1.0%
1.4%
572
3,964
0.5%
0.1%
0.3%
9,325
-10,881
2.1%
0.9%
-0.8%
-
Economic considerations
In 2006, the National Institute for Health and Disability Insurance reimbursed 25.4
million EURO for collection and interpretation of Pap smears from the uterine cervix
(0.4 million for collection by GPs, 3.9 million for collection by specialists and 21.6
million for cytological interpretation). In total, 1.3 million smears were interpreted
that year.
In the period 2004-06 (see Table 9), 1.7 million in the target population of 25-64 years
old women received at least one Pap smear but 3.2 million smears were interpreted in
this target population. However, 1.1 million women of the target population were not
screened at all during that three-year period.
Assuming that 10 % of screened women had cervical abnormalities requiring on
average 2 follow-up Pap testsl, we can estimate that about 380,000 Pap smears were
l
In fact the proportion of smears for reason of clinical follow-up is not known for Belgium.
Nevertheless, according to an analysis of data from the provincial cervical cytology registers of
Flemish-Brabant and Antwerp for the period 1996-97, 91% of smears were taken for screening, 4% for
clinical indications and 6% for follow-up. This estimate should be considered with caution since the
variable “reason for the Pap smear” was only available for 67% of the registered cytological records
(28).
83
taken yearly that do not contribute to screening coverage or follow-up. This
corresponds with an estimated 7.9 million € per year reimbursed by the NIHDI for
taking and reading Pap smears with limited clinical utilitym.
Moreover, in the period 2004-2006, 0.7 million smears were taken from women
beyond the target age range, representing a yearly expenditure of 4.7 million EURO
for the NIHDI, without accounting for the costs of medical consultations.
m
The average unit cost at charge of the National Institute for Health and Disability Insurance for one
smear was computed by dividing the total NIHDI expenditure of 2006 for collection and interpretation
of smears by the total number of corresponding acts: € 3.69 for collection and € 16.80 for
interpretation.
84
90%
80%
3-year screening coverage
70%
60%
50%
40%
30%
20%
HIS, 2004
10%
Individual patient files from IMA (2004)
0%
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75+
Age group
Figure 43. Estimation of the 3-year cervical cancer screening coverage estimated from the national health interview survey (HIS) in 2004 [blue curves, with 95% confidence
intervals in interrupted lines] and the corresponding coverage computed from individual health insurance date for the same year [red curve], Belgium, by age group.
85
30
1,400,000
1,200,000
25
1,000,000
15
600,000
6
800,000
Costs (*10 EURO)
Number of Pap smears
20
10
400,000
Number of Pap smear interpretations
200,000
5
Costs for interpretation of smears
Costs for taking & interpretation of smears
cvxriziv.xls/Pap_cht
0
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
0
2009
Year
Figure 44. Intensity and health insurance cost of cervical cancer screening in Belgium between 1983 en 2009: number of Pap smears interpreted (red curve) and costs for
interpretation (blue squares) and for collection & interpretation of cervical smears (NIHDI/IPH).
86
4,500,000
450,000
Number of colposcopies
Costs
3,500,000
Expences (€)
Number of colposcopies
400,000
350,000
300,000
2,500,000
250,000
200,000
1984
1,500,000
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Year
Figure 45. Number of colposcopic examinations performed and expenses for colposcopy spent between 1984 and 2009 in Belgium, as registered in the reimbursement
statistics of the National Institute for Health and Disability Insurance.
.
87
8.3.2. Colposcopies
In Table 36, we compare the number of colposcopies derived from the two databases.
In general, the differences (NIHDI-IMA-AIM) were smaller in the period 2002-06
(range: -0.3%-+2.4%) than in period 1996-2000 (range: -5.0%-+5.9%), as positive in
1996.
Table 36. Number of colposcopies by year reported by the National Institute for Health and Disability
Insurance (NIHDI) and computed from the individual patient data provided by IMA-AIM.
Year
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
NIHDI
IMA-AIM
402,697
378,750
393,002
398,704
395,688
408,634
393,745
410,083
394,187
413,785
407,511
397,447
395,598
399,462
396,828
406,028
401,457
402,218
403,370
392,942
383,674
NIHDI-IMA- Proportional
AIM
difference
23,947
5.9%
-5,702
-1.5%
-12,946
-3.3%
-16,338
-4.1%
-19,598
-5.0%
1,849
0.5%
2,634
0.7%
4,571
1.1%
-1,152
-0.3%
9,268
2.4%
The consumption of colposcopic examinations in Belgium is huge. On average, one
colposcopy is performed for every 3 Pap smears. The ratio of the number of Pap per
colposcopy has increased slightly: 3.0 in 1996-2000 versus 3.2 in 2002-06.
Nevertheless the capital reimbursed by the NIHDI (4.2 million € in 2009) is not so
elevated given the low unit price of colposcopy (10.85 € in 2006).
88
8.3.3. Hysterectomies
The total number of total hysterectomies performed in Belgium each year between
2001 and 2006, reported by the NIHDI and derived from the IMA-AIM file is shown
in Table 37n. The difference between IMA-AIM’s data and NIHDI’s data find its
explanation in the source of the data. IMA-AIM’s data are registered the day the act is
realised. NIHDI’s data are recorded the date of the reimbursement of the act.
Table 37. Number of total hysterectomies and cervix amputations by year reported by the National
Institute for Health and Disability Insurance (NIHDI) and computed from the individual patient data
provided by IMA-AIM.
Year
2001
2002
2003
2004
2005
2006
NIHDI
18,554
17,468
16,669
17,440
16,660
16,117
NIHDI- Proportional
IMA-AIM IMA-AIM difference
17,700
-232
-1.3%
16,785
-116
-0.7%
16,897
543
3.1%
16,454
206
1.2%
15,706
411
2.6%
In Figure 46 we give the trend in the number of all types of total hysterectomy and
cervix amputation performed each year in Belgium according to available statistics
published by the National Institute for Health and Disability Insurance.
n
Data from the previous study (1996-2000) are not shown since laparoscopic hysterectomies were not
included.
89
24,000
number of interventions
20,000
16,000
12,000
8,000
4,000
0
1984
1989
1994
1999
2004
year
Total abd. hysterectomy
Total vag. hysterectomy
Laparascopic & laparascopically assisted vaginal hysterectomy
Wertheim
Total hysterectomy & pelvic lymphadenectomy
Amputations cervix
Amputation resting cervix
Total
Figure 46. Number of total hysterectomies and cervix amputations performed each year in Belgium
between 1983 and 2009, according to the statistics published by the National Institute for Health and
Disability Insurance.
90
2009
8.4. Prevalence of cytological cervical lesions
In the framework of the Flemish cervical cancer screening programme, a cytological
register was set up. In Table 38, we show the overall distribution of cytological
findings and the range of minimum and maximum values from the first results from
provinces (29). For more details, we refer to a chapter on cytological registration in
Gezondheidsindictoren 1997, published by the Ministerie van de Vlaamse
Gemeenschap (28). More recent data are available from the provincial cervical
cytology registry of Limburg (see Table 39) (30). A substantial increase in the
occurrence of minor cytological abnormalities was noted in the second 5-year period
compared to the first one (30).
The prevalence of cytological abnormalities is indicative to estimate the need for
follow-up cytology, colposcopy and histology.
Table 38. Distribution of specimen adequacy and cytological abnormalities, as registered from
laboratories in Flemish-Brabant and Antwerp (1996-1998).
Distribution of specimen adequacy
% Sub-optimal
Inadequate
% without endocervical cells
Prevalence of squamous lesions
ASCCUS
Low-grade SIL
High-grade SIL
Suspicion of cancer
Presence of glandular lesions
AGUS, atypia, suspicion adenoca
Flemish-Brabant
Antwerp
N=175,260
N=47,721
38.5 (3.5-46.1)
0.6 (0.1-1.7)
27.2 (0.1-42.8)
25.7 (4.1-41.8)
0.7 (0.0-1.5)
21.3 (2.6-36.6)
1.6 (0.9-3.6)
0.7 (0.4-1.2)
0.5 (0.3-0.8)
0.17
2.1 (0.1-4.3)
1.1 (0.2-2.4)
0.5 (0.1-1.0)
0.06
0.6 (0.0-14.6)
1.8 (0.0-7.6)
Table 39. Distribution of specimen adequacy and cytological abnormalities, as registered by the
provincial cervical cytology registry of Limburg (1996-2005).
1996-2000
2001-2005
N=305,513
N=196,000
Distribution of specimen adequacy
% Sub-optimal
Inadequate
% without endocervical cells
Prevalence of squamous lesions
ASCCUS
Low-grade SIL
High-grade SIL
Suspicion of cancer
0.6
-
1.2 (0.0-1.2)
-
1.8 (0.1-5.2)
0.5 (0.1-1.2)
0.3 (0.1-0.8)
0.02 (0.00-0.09)
2.8 (0.2-18.6)
2.3 (0.1-7.1)
0.5 (0.1-1.1)
0.02 (0.00-0.04)
Presence of glandular lesions
AGUS, atypia, suspicion adenoca
0.1 (0.0-0.6)
0.1 (0.0-0.2)
91
8.5. Conclusions
Screening coverage in Belgium, the regions and provinces
The cervical cancer screening coverage, defined as the proportion of the target
population of women between 25 and 64 years old, that had a Pap smear taken in the
last 3 years, measured in 2006, was 61%. Similar to the preceding report , the range
of variation in screening coverage at the level of the regions was small: 60% in the
Flemish Region, 62% in the Brussels-Capital Region and 63% in the Walloon Region.
Differences at provincial levels are larger and range from 51% (Luxembourg) to 70%
(Walloon-Brabant).
Overall, the screening coverage increased with 2.2% compared to 2000. The increase
was largest in the Brussels-Capital region (+4.3%) and between 2 and 3% for the
other two regions. In most provinces, the screening coverage increased slightly
(between 0.9% and 4.3%), at the exception of two provinces where a small decrease
was noted (Limburg [-0.2%] and Luxembourg [-0.3%].
Age groups
At the national level, the youngest age groups of the target population (25-34 years),
were the best screened with a coverage of 70%. From the age of 35 to 49, the
coverage decreased gradually from 67% to 62%. From the age of 50, the coverage
dropped more steeply to reach a level of 44% in age group 60-64. The age profile
was similar in the three regions. However, in the Brussels-Capital and Walloon
Region the decline in the age group 50-64 was less pronounced than in the Flemish
Region.
Social status
Remarkable contrasts were noted between women who benefit or not from increased
reimbursement for health care (Beneficiary of Increased Reimbursement (BIR))o. In
the whole Belgian target age population, the screening coverage was respectively 40%
and 64% in women with and without the BIR status.
Comparison with interview surveys
The coverage computed from the individual health insurance data file is substantially
lower than the estimates derived from the national health interview surveys. For
instance at national level, for the years 2002-2004, this difference was 11.5%. This
discrepancy was already observed in the previous report and is probably due to
reporting biases, which are inherent to interview surveys. Also in the international
literature, self-reported screening status systematically appears to be overestimated
compared to the true coverage.
Target age range
Ten percent of all interpreted Pap smears are taken from women younger than 25
years and 8% in women older than 64 years.
o
Beneficiary of Increased Reimbursement (BIR), in Dutch: Rechthebbenden op de verhoogde
verzekeringstegemoetkoming (RVV); in French: Bénéficiaire de l’intervention majorée (BIM)
92
Screening interval
The modal screening interval was 12-15 months. A time span of 36 months or more
is observed in only 3 % of women with 2 or more smears in the studied time period,
whereas in 30% it was less than 12 months. This latter proportion decreased by age.
Pap smear excess use
In Belgium, screening is essentially opportunistic resulting in a high level of over
screening. The amount of used smears is theoretically sufficient to cover more than
100% of the target population over a time span of 3 years. Nevertheless, only 61% is
covered with one or more smears.
In absolute figures: 3.2 million Pap smears were interpreted in the period 2004-2006
which were taken from only 1.7 million women in the age range 25 to 64 years. 1.1
million women did not get a Pap smear. The excess use of cervical cytological
examinations was 88%, which means that each screened woman received 1.88 smears
over a 3-year period. The excess smear use was high in all parts of Belgium: it was
less high in the Flemish Region (84%), compared to the Brussels-Capital (95%) and
the Walloon Region (94%). Of course, a part of this “excess use” is used for followup of women with previous cervical abnormality. Assuming that 10% of the screened
women needed on average two follow-up Pap smears, we can estimate that yearly
about 380,000 Pap smears were taken that did not contribute to screening coverage or
follow-up. This corresponds with an estimated amount of € 7.9 million per year
reimbursed by the National Institute for Health and Disability Insurance (NIHDI) for
taking and reading Pap smears with limited utility. This amount is further increased
with € 4.7 million for screening beyond the target age range.
Colposcopy use
An impressive amount of colposcopies are performed in Belgium. At the national
level, on average, one colposcopic examination is done for every 3 Pap smears. In the
Walloon Region the ratio of the number of Pap smears over the number of
colposcopies is even less than two, whereas for the Flemish Region this ratio is five.
The biopsy/colposcopy ratio is low (on average 5%) which is due to the very high
frequency of colposcopy in women without a pathological pap smear.
It is clear that colposcopy is not used as indicated in national or international
guidelines. Colposcopic exploration is indicated in case of a first observation of
HSIL, glandular abnormality, or LSIL (certain countries like USA) or after a second
observation of ASC-US or LSIL (certain countries like UK) or after a positive HPV
triage result in ASCUS-cases and in follow-up after treated lesions (31-37).
General conclusion
In Belgium, cervical cancer screening is essentially opportunistic. The cervical cancer
screening coverage in Belgium, defined as the proportion of women in the 25-64 year
age range that received a Pap smear in the last 3 years, is only 61%. This is
2% higher compared to 2000. Nevertheless, the amount of smears used is
theoretically sufficient to cover the whole target population.
Estimation of the cervical cancer screening coverage, derived from interview surveys
should be interpreted with caution, given the inherent risk of overestimation.
93
Colposcopy is too often used simultaneously with the Pap smear, whereas its main
clinical indication is the exploration of women with previous cytological abnormality.
The excess use of colposcopy is most important in the Walloon region.
Because of the excess use the amount of smears used is theoretically sufficient to
cover the whole target population. Structural reduction of excess use and reinvestment in coverage and quality improvement can potentially result in more lifeyears saved, without an important increase in NIHDI funding.
Measures foreseen in the European Council Recommendation on Cancer screening (4)
and in the European Guidelines on Quality Assurance (5,38) should be binding and
universal. The fact that hardly any increase in screening coverage was observed over
the last ten years, demonstrates the necessity of an organised cervical cancer screening
programme. Health authorities of the Federal and Community Governments and
representatives of the scientific societies should meet as soon as possible in order to
define a rational, evidence-based and cost-effective cervical cancer screening policy.
In the context of the actual opportunistic screening, an organized cervical cancer
screening programme should deal with the crucial questions linked with the two major
problems identified in the current study.
1) How can the excess consumption of Pap smears among currently screened
women be reduced?
2) How can the 39% of the target population that is currently not covered be
reached and convinced to participate regularly (every three years)?
The Flemish Community has expressed the intention to tackle the problem and has set
up a technical working party. A major step to achieve complete and timely
registration of cancer screening data was the recent extension of the Belgian Law on
cancer registration foreseeing general registration of all cytopathology acts in the
framework of early detection of cancer (30,39). It must be remarked that organized
population screening, includes by definition registration of individual data with the
possibility of linkage between population-, cancer screening- and mortality-registers
(4,40). Moreover the Belgian privacy protect law foresees derogation specifically for
population screening (41).
These measures were foreseen in the framework of the Belgian Cancer Plan.
94
8.6. Propositions for further research
The discrepancy between the cervical cancer screening coverage, estimated from the
national health interview surveys and the coverage computed from individual patient
data provided by IMA-AIM, merits further research. An individual data linkage
between the health survey records and health insurance data files might be an
interesting initiative.
The reason for smear taking is insufficiently known. We have assumed that 10% of
the excessive smears could be clinically indicated because of a previous minor
cervical abnormality or for surveillance after treatment of a high-grade lesion. This
10% was based on previous analyses of provincial screening registers (42,43).
Linkage between health insurance files (allowing distinction between screening and
follow-up, since July 2009) and the systematic registration of cytological screening
and histological follow-up data (mandatory since 2010) will create the possibility to
assess this more precisely.
The discrepancy between number of cervical smears taken and interpreted merits
further investigation as well, preferentially using data files with exact calendar data.
The evaluation of effectiveness of cervical cancer screening requires operational
information systems allowing the linkage of personal screening and follow-up data
with the cancer register and mortality registers, as recommended in by the European
Council. The recent creation of a framework for comprehensive cytopathology
registration within the Belgian cancer registry, including all Pap smears and tissue
examination of cervix uteri offers enormous possibilities for evaluation of
interventions and research.
HPV testing is reimbursed in Belgium in case of ASC-US and in the follow-up after
treatment of high-grade CIN. Screening and follow-up registries should be extended
to allow registration of the results of HPV testing as well.
Since November 2006, HPV vaccination is reimbursed in Belgium (for girls 12-15
years old, extended to 18 years since December 2008), and since September 2010,
systematic free vaccination is offered in the Flemish Community for girls at school
(44,45). Comprehensive registries should be set up to include all individual
administrations of the HPV vaccine and these vaccination registries should be linked
with screening registries and with the cancer registry (46). Moreover, the careful
analysis of linked databases should be completed with a careful surveillance of the
effects of HPV vaccination, involving genotyping of cervical cell samples and
biopsies collected in the framework of cervical cancer screening (47). This
surveillance should assess impact of vaccination on the occurrence of HPV-induced
cervical cancer precursors, the duration of protection offered by the vaccine and
occurrence of HPV-type replacement. Such surveillance was started in 2010 as
collaboration between the Scientific Institute of Public Health and the International
Centre of Reproductive Health.
95
9. Glossary
Screening coverage
Proportion of women having had a Pap smear within the period indicated by the
screening interval. Formula: # women with Pap < x time ago / midyear population
over period x. Global population coverage is computed for the 25-64 year age group.
For age-specific coverage, the age group reached at the end of the interval is
considered.
# smears / # women ratio
Ratio of the number of smears to the size of the mid-year population of women in a
given period.
Excess smear use and overuse
The percentage of all Pap smears that does not contribute to the coverage considered
over a certain screening interval, in this case 3 years, in a target age group.
Formula: [total number of smears taken in the target age group during a screening
period)*100 / number of smears needed to reach the observed screening coverage] 100% (48).
“Overuse” is a related indicator: ratio of the number of smears taken in the target age
group during a screening period/number of smears needed to reach the observed
screening coverage. Overuse was computed and discussed in the previous report (17).
(Overuse-1)*100 gives the “excess use” as a percentage.
Target population
The population of women at risk for cervical cancer, for whom screening is
recommended. In the European Guideline for Quality Assurance in Cervical Cancer
Screening cytological screening is recommended to target the age groups 25 to 64
years (5,49).
Real target population
Population of women between 25-64 years, still having a cervix. The real target
population is computed as following: Popi* (1-Cumulative Incidence of total
hysterectomy up to agei.), where i is the index for 5-year age group.
Recommended screening interval
Period between 2 successive smears according to the screening policy, which is for
Belgium 3 years. The screening interval recommended in the European Guideline for
Quality Assurance in Cervical Cancer Screening is three to five years.
In this report we also compute the screening coverage and consumption of Pap smears
over a 1-year period, which, in opportunistic screening, is the usual interval.
Throughout the report it is always specified which screening interval is considered.
96
10. Abbreviations
ASC-US: atypical squamous cells of unspecified significance
AGUS: atypical glandular cells of unspecified significance
BIM: Bénéficiaire de l’intervention majorée
BIR: beneficiary of increased reimbursement
CI: 95% confidence interval
DGSEI: Directorate-general Statistics and Economic Information
EU: European Union
GP: general practitioner
HIS: Health Interview Survey
HSIL: high-grade squamous intra-epithelial lesions
IHID: individual health insurance data.
IMA-AIM: Intermutalistisch Agentschap – l’Agence Intermutualiste
IPH: Scientific Institute of Public Health
ISP: Institut scientifique de Santé public.
LSIL: low-grade squamos intra-epithelial lesions
NIHDI: National Institute for Health and Disability Insurance
NIS: National Institute of Statistics
RIZIV. Rijksinstituut voor Ziekte en Invaliditeitsverzekering
RVV: Rechthebbende op verhoogde verzekeringstegemoetkoming
WIV: Wetenschappelijk Instituut Volksgezondheid
97
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101
12. Annexes
12.1. Definition of the BIR (BIM-RVV) status
Octroi du statut BIM en 2006
Veufs/veuves
Invalides
Pensionné(e)s
TRN > 65 ans (Titulaire du
Registre National)
Conditions de qualité et de revenus :
13.246,34 EUR
+ 2.452,52 EUR Par personne à charge
Agents des services publics en
disponibilité
Orphelins
Handicapés sans allocation
Bénéficiaires d’allocations
familiales majorées
Chômeurs âgés de longue durée
Les membres des communautés
religieuses de 65 ans et +
Bénéficiaires du RIS (revenus
d'intégration social)
de l’aide équivalente au RIS
Uniquement condition de qualité
d’un revenu garanti aux personnes
âgées
d’une allocation pour handicapé
102
Toekenning van de RVV status in 2006 (Rechthebbenden op de Verhoogde
Verzekerings tegemoetkoming van het RIZIV)
Weduwenaar/weduwe
Invalide
Gepensioneerde
Als resident ingeschreven en
minstens 65 jaar oud
Persoonlijke omstandigheden en
inkomen
Ambtenaar die in disponibiliteit
gesteld werd
13.246,34 EUR
+ 2.452,52 EUR per persoon ten laste
Wees
Gehandicapte zonder sociale
uitkering
Verhoogde kinderbijslag
Volledig langdurig werkloos
lid van een kloostergemeenschap
Rechthebbenden op een leefloon
van het OCMW
Sociale hulp, toegekend door het
OCMW
Zonder inkomensvoorwaarde
Inkomensgarantie voor ouderen, of
rentebijslag
Vergoeding van de FOD Sociale
Zekerheid als gehandicapte
103
12.2. Pap smears with limited utility and their associated
costs for NIHDI
Calculation of costs spent by NIHDI on ‘non-necessary’ Pap smears (excess Pap
smears to cover a 3-yearly interval and Pap smears outside the target age group) was
done as follows:
Excess Pap smears to cover a 3-yearly interval:
(Tabel 9)
The total number of Pap smears in 2004-2006 (25-64y):
Number of women screened <3years ago (25-64y):
3,199,984
1,706,043
Pap smears not contributing to screening in the 3-year time interval (excess Pap
smears):
3,199,984-1,706,043 = 1,493,941
Per year:
1,493,941/3 = 497,980.33
*Assuming that 5% of screened women need on average two follow-up smears
because of cervical abnormalities:
2*5% of 1,706,043= 170,604 repeat Pap smears/3year= 56,868 Pap smears/year.:
497,980 - 56,868 = 441,112 (≅ 440,000 Pap smears)
*Assuming that 10 % of screened women need on average two follow-up smears
because of cervical abnormalities:p
2*10% of 1,706,043/3 years = 113,736 Pap smears / year
excess smears/year:
497,980-113,736= 384,224 (≅ 380,000 Pap smears)
Pap smears outside the target age group (2004-2006):
Age group
10-14
15-19
20-24
65-69
70-74
75+
Total
p
Number of
Pap smears
1,517
91,108
300,981
142,924
88,892
68,634
694,056
No exact data are available concerning the proportion of Pap smears that are used for screening or for
follow-up. For the report, we have focused on the 2nd assumption (10% of screened women have
screen detected abnormalities or are in post treatment follow-up needing on average two further Pap
smears).
104
Per year:
694,056/3 = 231,352
Associated costs for NIHDI:
q
Total number of smear in 2006, taken by
a general practitioner:
a gynaecologist:
Total number of smears in 2006, read:
111,427
1,034,878
1,284,425
total cost in 2006 for taking of a smear by
a general practitioner:
a gynaecologist:
total cost in 2006 for reading of a smear:
374,533 euro
3,856,935 euro
21,581,395 euro
Mean cost for taking of a smear (GP and gynaecologist taken together):
Total costs / total number of smears taken
(374,533 euro+3,856,935 euro) / (111,427+1,034,878) = 3.69 euro/smear
Mean cost for reading of a Pap smear:
Total costs / total number of smears read
21,581,395 euro / 1,284,425 = 16.80 euro/reading
Mean cost of Pap smears overall:
costs taking + costs reading
3.69 euro + 16.80 euro = 20.49 euro
Estimated costs for taking and reading of excess Pap smears:
5% of screened women needing 2 follow-up smears:
441,112 ‘non-necessary’ Pap smears * 20.49 overall cost = 9,040,056.5 euro
10% of screened women needing 2 follow-up smears:
384,224 ‘non-necessary’ Pap smears * 20.49 overall cost = 7,874,613.4 euro
Estimated costs for Pap smears outside the target age range:
231,352 Pap smears * 20.49 overall cost = 4,740,402.5 euro.
q
The amount of cervical interventions and associated costs are annually communicated by NIHDI.
105
12.3. Cervical cytology use by one-year intervals, by age and
region
Table 40. Ratio of the number of Pap smears / number of women with at least one Pap smear and
coverage calculated over one-year periods and by 5-year age group (Belgium, 2002-2006).
2002
2003
2004
2005
2006
Age
group
ratio
coverage
ratio
coverage
ratio
coverage
ratio
coverage
ratio
coverage
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
0.00
0.09
0.31
0.42
0.44
0.41
0.40
0.38
0.36
0.33
0.24
0.17
0.11
0.2%
8.8%
28.7%
38.9%
40.6%
38.5%
37.1%
35.9%
34.1%
30.6%
23.0%
16.2%
10.3%
0.00
0.10
0.31
0.43
0.44
0.41
0.40
0.38
0.36
0.32
0.25
0.18
0.11
0.2%
9.1%
29.1%
39.6%
40.8%
38.5%
37.5%
36.0%
33.5%
29.8%
23.4%
17.2%
10.4%
0.00
0.10
0.32
0.44
0.45
0.42
0.40
0.39
0.36
0.31
0.25
0.18
0.11
0.2%
9.4%
29.6%
40.4%
41.2%
39.1%
38.0%
36.5%
33.7%
29.6%
24.0%
17.5%
10.7%
0.00
0.10
0.31
0.44
0.44
0.42
0.41
0.39
0.36
0.31
0.26
0.18
0.11
0.2%
9.5%
29.3%
40.8%
40.8%
39.6%
38.1%
36.4%
33.8%
29.6%
24.3%
17.5%
10.7%
0.00
0.10
0.31
0.43
0.44
0.42
0.40
0.39
0.36
0.30
0.27
0.18
0.11
0.1%
9.5%
29.2%
40.0%
40.6%
39.4%
37.7%
36.5%
33.7%
28.4%
25.4%
17.2%
10.9%
75-79
0.09
8.3%
0.09
8.6%
0.10
9.1%
0.10
9.5%
0.10
9.6%
106
Table 41. Ratio of the number of Pap smears / number of women with at least one Pap smear and
coverage calculated over one-year periods and by 5-year age group and per region (Belgium, 20022006).
2002
Age
group
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
ratio coverage ratio
Flemish Region
0.00
0.2% 0.00
0.07
7.0% 0.07
0.27
25.5% 0.27
0.40
37.2% 0.41
0.42
39.7% 0.43
0.40
37.9% 0.40
0.38
36.4% 0.39
0.36
34.4% 0.37
0.34
31.9% 0.33
0.29
27.6% 0.28
0.22
20.5% 0.22
0.14
13.2% 0.15
0.08
7.5% 0.08
0.06
5.6% 0.06
Brussels-Capital Region
0.00
0.3% 0.00
0.10
9.1% 0.10
0.32
29.1% 0.31
0.42
37.4% 0.43
0.44
39.8% 0.45
0.42
37.7% 0.42
0.41
37.6% 0.41
0.41
37.7% 0.41
0.40
37.0% 0.40
0.38
35.0% 0.37
0.31
28.9% 0.31
0.25
24.0% 0.26
0.19
17.8% 0.19
0.17
15.8% 0.18
Walloon Region
0.00
0.2% 0.00
0.12
11.3% 0.12
0.36
33.3% 0.36
0.44
40.4% 0.45
0.45
41.3% 0.45
0.42
38.8% 0.42
0.40
37.6% 0.41
0.40
37.4% 0.40
0.39
36.4% 0.38
0.37
34.6% 0.36
0.27
25.6% 0.28
0.20
19.1% 0.22
0.13
12.4% 0.13
0.10
9.5% 0.11
2003
2004
2005
2006
coverage
ratio
coverage
ratio
coverage
ratio
coverage
0.2%
7.1%
25.8%
38.1%
39.9%
37.9%
36.6%
34.6%
31.4%
26.7%
20.7%
14.2%
7.8%
5.9%
0.00
0.08
0.28
0.42
0.43
0.41
0.40
0.37
0.33
0.28
0.23
0.15
0.09
0.07
0.1%
7.3%
26.3%
39.1%
40.4%
38.3%
37.4%
35.2%
31.6%
26.9%
21.7%
14.5%
8.2%
6.3%
0.00
0.08
0.28
0.42
0.43
0.42
0.40
0.37
0.34
0.28
0.23
0.15
0.09
0.07
0.1%
7.3%
26.1%
39.3%
39.9%
39.1%
37.5%
35.0%
31.9%
26.9%
22.1%
14.6%
8.4%
6.7%
0.00
0.08
0.28
0.41
0.43
0.41
0.39
0.38
0.34
0.28
0.24
0.15
0.09
0.07
0.1%
7.3%
26.1%
38.8%
40.1%
39.0%
37.3%
35.6%
32.0%
26.3%
22.7%
14.7%
8.6%
7.0%
0.3%
9.4%
28.4%
38.7%
40.2%
38.1%
37.9%
37.5%
37.1%
34.0%
29.2%
24.5%
18.0%
16.6%
0.00
0.10
0.32
0.43
0.45
0.43
0.41
0.41
0.39
0.36
0.31
0.26
0.18
0.18
0.3%
9.0%
28.6%
38.4%
40.5%
39.1%
37.8%
37.7%
36.4%
33.4%
29.2%
24.8%
17.5%
17.4%
0.00
0.10
0.30
0.43
0.44
0.43
0.40
0.40
0.38
0.35
0.30
0.25
0.18
0.18
0.2%
9.1%
27.2%
38.5%
39.7%
38.5%
37.2%
37.4%
35.7%
32.6%
28.6%
23.9%
17.4%
17.5%
0.00
0.10
0.29
0.40
0.43
0.41
0.40
0.39
0.38
0.33
0.32
0.24
0.18
0.18
0.2%
8.9%
26.7%
36.1%
38.6%
37.2%
36.5%
36.3%
35.6%
31.1%
29.8%
23.1%
17.2%
17.5%
0.2%
11.6%
33.7%
41.3%
41.5%
38.9%
38.3%
37.7%
35.8%
33.8%
26.3%
20.6%
12.6%
10.0%
0.00
0.13
0.38
0.46
0.46
0.43
0.41
0.41
0.39
0.35
0.28
0.22
0.14
0.12
0.2%
12.2%
34.7%
42.5%
42.1%
39.8%
38.5%
38.1%
36.2%
33.0%
26.6%
20.9%
13.1%
10.9%
0.00
0.13
0.37
0.48
0.46
0.43
0.42
0.41
0.38
0.35
0.29
0.22
0.14
0.12
0.2%
12.7%
34.7%
43.6%
42.0%
40.2%
38.9%
38.1%
36.2%
33.1%
27.1%
21.1%
13.1%
11.5%
0.00
0.14
0.37
0.47
0.45
0.43
0.41
0.40
0.38
0.32
0.30
0.21
0.14
0.12
0.1%
12.8%
34.6%
42.9%
41.3%
40.1%
38.0%
37.7%
35.6%
30.8%
29.0%
20.3%
13.0%
11.5%
107
12.4. Cervical cytology use by three-year intervals, by age
and province
Table 42. 3-year screening coverage, ratio of # smears / # women and excessive use of Pap smears,
computed for the period 2002-04 and 2004-06 (Belgium).
Belgium
Age
(years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
108
2002-04
Coverage
0.5%
16.8%
51.2%
67.9%
69.7%
65.8%
64.5%
61.4%
56.4%
51.2%
40.8%
30.5%
19.9%
18.7%
2004-06
# smears/# women
ratio
0.01
0.22
0.85
1.23
1.30
1.23
1.20
1.16
1.09
1.00
0.76
0.57
0.35
0.30
Excess
use
13.1%
32.5%
65.5%
81.4%
85.9%
86.3%
86.7%
89.4%
93.7%
95.4%
87.5%
86.0%
77.3%
59.3%
Coverage
0.3%
17.4%
51.7%
69.7%
69.6%
67.2%
64.8%
62.0%
57.1%
49.4%
44.1%
31.1%
20.6%
20.3%
# smears/# women
ratio
0.00
0.23
0.86
1.27
1.29
1.26
1.21
1.17
1.10
0.95
0.83
0.57
0.36
0.32
Excess
use
8.2%
33.8%
65.8%
82.0%
85.8%
87.0%
86.8%
88.9%
92.4%
91.9%
88.1%
82.5%
76.0%
59.3%
computed for the period 2002-04 and 2004-06 (Belgium, by region).
Flemish
Region
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
BrusselsCapital
Region
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
2002-04
Coverage
0.4%
13.8%
47.1%
67.4%
69.1%
65.4%
64.2%
60.3%
54.2%
47.5%
38.2%
26.5%
16.0%
13.7%
2004-06
# smears/# women
ratio
0.00
0.18
0.75
1.18
1.26
1.20
1.18
1.12
1.03
0.90
0.69
0.48
0.27
0.21
2002-04
Coverage
0.7%
16.6%
49.8%
65.8%
69.4%
65.6%
63.7%
62.0%
59.4%
55.0%
47.3%
40.5%
30.8%
34.7%
Excess use Coverage
12.7%
0.3%
27.4%
14.1%
58.6%
47.7%
75.6%
69.1%
81.8%
69.1%
83.6%
66.8%
84.2%
64.8%
86.3%
61.1%
90.0%
55.3%
89.3%
46.6%
81.0%
41.2%
80.6%
27.2%
71.5%
16.9%
53.7%
15.3%
# smears/# women
ratio
0.00
0.18
0.76
1.22
1.25
1.23
1.19
1.14
1.04
0.87
0.75
0.48
0.29
0.24
Excess
use
7.1%
28.5%
58.6%
76.4%
81.5%
84.3%
84.2%
86.0%
88.9%
86.5%
82.0%
77.8%
71.2%
53.9%
# smears/# women
ratio
0.01
0.23
0.82
1.21
1.33
1.28
1.23
1.21
1.19
1.06
0.99
0.78
0.58
0.61
Excess
use
5.9%
38.7%
69.6%
84.2%
93.3%
94.9%
95.4%
95.7%
100.5%
102.3%
101.7%
95.8%
88.2%
67.5%
2004-06
# smears/# women
ratio
0.01
0.23
0.85
1.23
1.36
1.29
1.25
1.24
1.21
1.14
0.97
0.81
0.59
0.59
Excess use Coverage
11.6%
0.6%
38.3%
16.3%
70.8%
48.5%
87.4%
65.4%
95.9%
68.7%
96.6%
65.9%
96.2%
63.1%
99.6%
61.7%
103.8%
59.4%
107.6%
52.2%
104.4%
49.0%
100.6%
39.7%
92.8%
31.0%
69.0%
36.3%
109
computed for the period 2002-04 and 2004-06 (Belgium, by region).
Walloon
Region
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
110
2002-04
Coverage
0.4%
21.8%
58.9%
69.7%
70.9%
66.6%
65.1%
63.3%
59.3%
57.0%
44.1%
35.9%
24.2%
22.3%
2004-06
# smears/# women
ratio
0.01
0.30
1.02
1.32
1.34
1.25
1.23
1.21
1.17
1.15
0.85
0.68
0.43
0.36
Excess use Coverage
14.4%
0.4%
36.7%
23.2%
73.9%
59.7%
88.8%
72.7%
89.4%
70.6%
88.2%
68.2%
88.8%
65.2%
91.9%
63.6%
96.8%
59.7%
101.6%
53.5%
93.7%
48.6%
89.4%
36.5%
79.0%
24.7%
60.8%
24.6%
# smears/# women
ratio
0.00
0.32
1.04
1.39
1.34
1.29
1.24
1.22
1.17
1.06
0.95
0.68
0.44
0.40
Excess
use
10.6%
38.0%
74.7%
90.8%
90.3%
89.4%
89.4%
92.2%
95.9%
97.3%
94.5%
85.6%
78.2%
61.6%
computed for the period 2002-04 and 2004-06 (Belgium, by province).
Antwerp
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Brussels
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
2002-04
Coverage
0.7%
14.4%
48.3%
68.8%
70.1%
67.4%
65.6%
61.4%
54.8%
48.1%
39.4%
25.0%
14.6%
13.1%
2004-06
# smears/# women
ratio
0.01
0.19
0.77
1.21
1.27
1.23
1.19
1.13
1.02
0.88
0.69
0.45
0.25
0.20
Excess
use
17.3%
28.1%
59.4%
75.7%
81.8%
82.5%
80.7%
83.6%
85.8%
83.0%
74.7%
81.2%
70.8%
53.1%
# smears/# women
ratio
0.01
0.23
0.85
1.23
1.36
1.29
1.25
1.24
1.21
1.14
0.97
0.81
0.59
0.59
Excess
use
11.6%
38.3%
70.8%
87.4%
95.9%
96.6%
96.2%
99.6%
103.8%
107.6%
104.4%
100.6%
92.8%
69.0%
2002-04
Coverage
0.7%
16.6%
49.8%
65.8%
69.4%
65.6%
63.7%
62.0%
59.4%
55.0%
47.3%
40.5%
30.8%
34.7%
Coverage
0.4%
14.3%
48.2%
70.8%
69.9%
68.7%
66.4%
62.7%
56.6%
47.8%
42.9%
25.8%
15.5%
14.3%
# smears/# women
ratio
0.00
0.19
0.77
1.25
1.27
1.26
1.20
1.14
1.05
0.86
0.75
0.46
0.27
0.22
Excess use
10.9%
30.3%
60.0%
76.6%
81.4%
83.9%
81.3%
82.5%
84.8%
79.9%
75.1%
78.1%
71.3%
54.7%
# smears/# women
ratio
0.01
0.23
0.82
1.21
1.33
1.28
1.23
1.21
1.19
1.06
0.99
0.78
0.58
0.61
Excess use
5.9%
38.7%
69.6%
84.2%
93.3%
94.9%
95.4%
95.7%
100.5%
102.3%
101.7%
95.8%
88.2%
67.5%
2004-06
Coverage
0.6%
16.3%
48.5%
65.4%
68.7%
65.9%
63.1%
61.7%
59.4%
52.2%
49.0%
39.7%
31.0%
36.3%
111
FlemishBrabant
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
WalloonBrabant
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
112
2002-04
Coverage
0.5%
15.0%
48.6%
68.6%
71.6%
68.2%
67.5%
64.8%
58.5%
53.7%
45.0%
33.6%
21.0%
17.6%
2004-06
# smears/# women
ratio
0.01
0.20
0.78
1.21
1.31
1.27
1.27
1.23
1.14
1.06
0.86
0.63
0.38
0.29
Excess
use
12.2%
30.4%
61.0%
76.4%
82.5%
86.8%
88.8%
90.6%
95.3%
97.5%
90.5%
87.0%
78.7%
63.2%
# smears/# women
ratio
0.01
0.34
1.18
1.53
1.60
1.50
1.49
1.44
1.39
1.38
1.12
0.90
0.58
0.45
Excess
use
30.9%
42.5%
90.9%
104.7%
103.6%
102.9%
103.5%
105.6%
110.9%
114.6%
107.2%
103.3%
88.8%
67.6%
2002-04
Coverage
0.8%
23.7%
61.9%
74.9%
78.5%
74.0%
73.4%
70.1%
65.7%
64.2%
54.2%
44.5%
30.8%
26.9%
Coverage
0.3%
15.2%
49.2%
69.6%
71.8%
70.0%
68.0%
64.9%
59.6%
53.2%
47.5%
34.1%
22.3%
19.3%
# smears/# women
ratio
0.00
0.20
0.79
1.23
1.30
1.30
1.27
1.23
1.15
1.02
0.90
0.63
0.39
0.31
Excess use
6.6%
30.4%
60.3%
76.6%
81.0%
85.8%
87.5%
89.9%
92.5%
92.4%
89.5%
84.3%
77.1%
61.6%
# smears/# women
ratio
0.01
0.35
1.16
1.54
1.57
1.55
1.47
1.45
1.38
1.26
1.18
0.89
0.59
0.51
Excess use
15.6%
43.3%
86.5%
105.5%
102.2%
101.6%
102.3%
103.6%
108.1%
108.5%
105.6%
98.9%
88.7%
67.7%
2004-06
Coverage
0.5%
24.7%
62.4%
74.9%
77.4%
76.7%
72.6%
71.0%
66.2%
60.6%
57.3%
44.6%
31.1%
30.3%
WestFlanders
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
EastFlanders
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
2002-04
Coverage
0.3%
13.0%
46.3%
66.6%
67.7%
63.4%
62.6%
58.1%
52.2%
43.0%
34.1%
23.3%
14.0%
12.1%
2004-06
# smears/# women
ratio
0.00
0.16
0.74
1.18
1.23
1.17
1.16
1.08
0.98
0.79
0.60
0.41
0.23
0.18
Excess
use
8.3%
27.1%
59.5%
77.1%
81.6%
83.9%
85.5%
85.4%
87.5%
85.0%
76.6%
75.5%
66.9%
46.5%
# smears/# women
ratio
0.00
0.18
0.76
1.21
1.31
1.25
1.22
1.15
1.05
0.92
0.68
0.47
0.28
0.22
Excess
use
6.1%
27.5%
60.7%
79.0%
87.4%
89.5%
90.9%
93.8%
98.7%
98.5%
92.3%
83.9%
76.1%
55.3%
2002-04
Coverage
0.3%
13.9%
47.3%
67.8%
69.7%
66.1%
64.1%
59.5%
52.8%
46.2%
35.2%
25.5%
16.1%
14.0%
Coverage
0.2%
14.0%
47.3%
68.9%
67.3%
64.6%
63.3%
59.5%
53.6%
42.6%
37.4%
24.3%
15.0%
13.6%
# smears/# women
ratio
0.00
0.18
0.75
1.22
1.22
1.18
1.17
1.11
1.00
0.78
0.66
0.42
0.25
0.20
Excess use
0.0%
27.8%
59.6%
77.3%
81.4%
83.3%
84.9%
86.1%
86.7%
82.9%
77.0%
73.1%
67.0%
49.9%
# smears/# women
ratio
0.00
0.18
0.78
1.25
1.31
1.30
1.25
1.17
1.08
0.88
0.77
0.48
0.29
0.25
Excess use
5.2%
28.1%
59.7%
79.3%
86.9%
91.1%
91.1%
93.4%
98.1%
96.2%
93.5%
82.4%
74.5%
54.0%
2004-06
Coverage
0.3%
14.2%
48.7%
69.7%
70.3%
68.1%
65.4%
60.6%
54.5%
44.6%
39.5%
26.3%
16.8%
16.3%
113
Hainaut
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Liège
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
114
2002-04
Coverage
0.4%
21.8%
58.0%
69.6%
70.4%
65.3%
62.4%
60.6%
57.1%
54.5%
41.3%
32.5%
20.5%
19.5%
2004-06
# smears/# women
ratio
0.00
0.30
1.01
1.31
1.32
1.21
1.16
1.15
1.11
1.09
0.80
0.61
0.36
0.30
Excess
use
8.8%
36.8%
73.5%
88.6%
88.1%
85.7%
85.2%
89.2%
93.9%
99.5%
92.7%
87.8%
77.0%
54.6%
# smears/# women
ratio
0.01
0.31
1.05
1.33
1.37
1.30
1.28
1.28
1.21
1.19
0.91
0.75
0.53
0.47
Excess
use
12.5%
36.6%
71.6%
85.7%
88.3%
87.8%
89.0%
91.4%
95.4%
99.1%
91.7%
87.0%
79.5%
64.8%
2002-04
Coverage
0.5%
22.8%
61.1%
71.4%
72.8%
69.2%
67.8%
66.8%
62.2%
59.6%
47.2%
40.2%
29.4%
28.4%
Coverage
0.3%
22.3%
59.2%
72.2%
69.8%
67.4%
63.1%
60.9%
57.7%
50.4%
46.3%
32.9%
21.4%
21.1%
# smears/# women
ratio
0.00
0.31
1.04
1.38
1.32
1.27
1.18
1.16
1.11
0.99
0.91
0.61
0.38
0.34
Excess use
4.2%
37.5%
75.0%
90.6%
89.5%
87.9%
86.8%
90.0%
93.1%
96.6%
96.3%
85.7%
78.3%
59.2%
# smears/# women
ratio
0.01
0.35
1.08
1.42
1.38
1.33
1.29
1.27
1.21
1.11
0.97
0.75
0.52
0.50
Excess use
12.4%
39.0%
73.1%
88.1%
88.6%
89.1%
89.4%
91.8%
94.8%
94.6%
91.0%
82.7%
75.7%
62.3%
2004-06
Coverage
0.5%
25.5%
62.2%
75.3%
73.1%
70.2%
68.1%
66.4%
62.0%
57.2%
50.9%
40.9%
29.4%
30.9%
Limburg
2002-04
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Coverage
0.1%
12.2%
44.0%
63.0%
64.5%
59.1%
59.7%
56.6%
52.1%
47.3%
38.2%
27.1%
14.9%
11.9%
Luxembourg
2002-04
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Coverage
0.2%
16.2%
49.1%
54.0%
52.3%
51.6%
54.5%
54.2%
50.5%
47.8%
35.0%
28.4%
17.8%
13.9%
2004-06
# smears/# women
ratio
0.00
0.15
0.66
1.05
1.10
1.00
1.02
0.99
0.94
0.85
0.64
0.46
0.23
0.17
Excess
use
6.7%
21.7%
49.3%
66.0%
70.3%
69.8%
71.7%
74.7%
80.1%
80.5%
68.0%
70.3%
56.0%
44.2%
# smears/# women
ratio
0.00
0.21
0.82
0.99
0.95
0.93
0.99
1.00
0.97
0.93
0.66
0.51
0.30
0.20
Excess
use
5.6%
32.1%
67.4%
82.8%
80.7%
79.8%
81.0%
83.8%
92.5%
94.7%
87.7%
80.9%
66.5%
47.2%
Coverage
0.1%
12.2%
44.1%
64.6%
64.4%
59.5%
58.4%
56.2%
50.6%
44.9%
38.0%
27.3%
16.1%
12.9%
# smears/# women
ratio
0.00
0.15
0.66
1.09
1.11
1.02
1.01
0.99
0.91
0.81
0.66
0.45
0.26
0.18
Excess use
0.0%
23.6%
50.6%
69.3%
72.3%
71.2%
72.4%
75.5%
79.6%
80.3%
73.1%
65.5%
59.2%
41.5%
# smears/# women
ratio
0.00
0.24
0.84
1.08
0.96
0.93
0.96
1.01
0.98
0.87
0.74
0.53
0.30
0.25
Excess use
25.0%
32.1%
66.3%
87.3%
82.0%
80.1%
83.0%
85.7%
90.7%
93.3%
82.1%
78.4%
65.4%
50.8%
2004-06
Coverage
0.1%
18.1%
50.4%
57.7%
52.9%
51.5%
52.4%
54.6%
51.6%
44.9%
40.6%
29.7%
18.2%
16.4%
115
Namur
Age (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
116
2002-04
Coverage
0.4%
21.4%
59.4%
71.1%
72.5%
66.5%
65.1%
62.1%
58.6%
56.1%
40.5%
32.9%
21.4%
18.2%
2004-06
# smears/# women
ratio
0.00
0.29
1.01
1.33
1.36
1.24
1.22
1.19
1.15
1.14
0.77
0.63
0.38
0.30
Excess
use
11.5%
33.4%
69.5%
87.0%
87.2%
86.3%
88.0%
92.0%
97.0%
103.3%
90.2%
90.7%
78.8%
65.4%
Coverage
0.3%
22.3%
58.3%
74.9%
72.3%
68.6%
65.6%
63.5%
59.3%
52.7%
45.9%
34.0%
22.2%
20.7%
# smears/# women
ratio
0.00
0.30
1.01
1.41
1.37
1.28
1.23
1.22
1.17
1.04
0.88
0.63
0.40
0.34
Excess use
10.5%
34.8%
72.6%
88.5%
89.8%
87.1%
87.5%
91.7%
97.3%
96.9%
92.7%
84.3%
81.4%
65.5%
12.5. 3-year Pap smear use by age group, province and BIR
status
Table 45. Screening coverage, #smears/#women ratio, excess use for women with BIR status=0 and 1,
by age-group for the whole of Belgium. Ratios of coverage BIR=0 / coverage BIR=1 and difference
coverage BIR=0 - coverage BIR=1.
BIR=0
Age
group
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
3-year
coverage
17.5%
53.9%
70.9%
73.1%
70.6%
67.4%
63.8%
59.5%
51.7%
45.4%
34.2%
23.0%
23.1%
#smears/
#women
ratio
0.24
0.89
1.29
1.36
1.33
1.27
1.21
1.16
1.01
0.87
0.64
0.41
0.38
Contrast 3-y
coverage
BIR=1
Excess
use
34.2%
65.6%
82.3%
86.3%
87.8%
87.8%
90.3%
95.3%
94.7%
0.91516
0.85796
0.79867
0.64981
3-year
coverage
15.8%
41.4%
47.5%
48.0%
47.1%
45.1%
43.8%
41.1%
36.3%
31.7%
23.7%
15.5%
13.4%
#smears/
#women
ratio
0.20
0.70
0.83
0.83
0.79
0.75
0.73
0.68
0.62
0.54
0.40
0.26
0.20
Excess
use
29.7%
68.1%
74.4%
72.0%
67.2%
67.1%
66.4%
64.7%
71.9%
70.1%
69.8%
64.5%
48.3%
Ratio
0.90
0.77
0.67
0.66
0.67
0.67
0.69
0.69
0.70
0.70
0.69
0.67
0.58
Difference
1.7%
12.5%
23.4%
25.1%
23.5%
22.4%
20.0%
18.3%
15.4%
13.7%
10.5%
7.5%
9.7%
117
by age-group and region. Ratios of coverage BIR=0 / coverage BIR=1 and difference coverage BIR=0 coverage BIR=1.
BIR=0
Region
Flemish
Region
Walloon
Region
BrusselsCapital
Region
118
Age
group
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
3-year
coverage
14.3%
49.9%
69.9%
73.1%
70.2%
66.9%
62.4%
56.9%
48.9%
42.6%
30.2%
19.0%
17.9%
23.4%
62.7%
76.1%
75.6%
73.0%
69.4%
66.8%
64.0%
56.4%
50.6%
41.2%
28.5%
27.4%
18.4%
55.9%
70.0%
74.8%
73.1%
71.0%
69.3%
67.5%
59.7%
55.1%
46.7%
37.1%
40.2%
#smears/
#women
ratio
0.18
0.79
1.24
1.33
1.30
1.24
1.17
1.09
0.92
0.79
0.54
0.33
0.29
0.33
1.09
1.46
1.44
1.39
1.32
1.30
1.28
1.13
1.00
0.78
0.52
0.46
0.26
0.95
1.29
1.45
1.43
1.40
1.38
1.40
1.25
1.16
0.95
0.72
0.69
Contrast 3-y
coverage
BIR=1
Excess
use
28.8%
58.9%
76.8%
82.0%
85.0%
84.9%
87.0%
90.8%
88.7%
84.9%
80.4%
74.8%
60.4%
38.8%
74.3%
91.2%
91.0%
90.4%
90.8%
94.1%
99.8%
100.8%
97.8%
89.2%
81.7%
66.3%
40.0%
70.3%
84.4%
93.9%
96.2%
97.4%
99.5%
107.8%
108.7%
109.9%
102.2%
93.5%
72.1%
3-year
coverage
10.6%
34.2%
40.6%
41.7%
41.1%
40.8%
39.8%
36.6%
33.4%
29.9%
20.9%
13.1%
10.4%
23.0%
49.7%
50.2%
49.4%
49.7%
47.5%
46.3%
43.4%
38.5%
33.7%
27.3%
18.8%
16.9%
10.9%
40.2%
55.7%
57.0%
55.2%
50.8%
48.5%
48.5%
41.4%
35.9%
29.9%
22.4%
24.8%
#smears/
#women
ratio
0.13
0.52
0.65
0.67
0.64
0.66
0.65
0.59
0.56
0.49
0.35
0.21
0.15
0.30
0.89
0.91
0.85
0.83
0.80
0.79
0.73
0.68
0.60
0.47
0.32
0.26
0.14
0.67
1.02
1.06
1.01
0.90
0.81
0.80
0.71
0.60
0.52
0.38
0.38
Excess
use
23.9%
53.1%
60.1%
60.4%
56.4%
60.7%
62.3%
60.3%
66.7%
65.2%
67.6%
60.8%
43.1%
32.1%
79.3%
81.6%
72.5%
68.0%
68.1%
69.8%
68.2%
76.8%
78.0%
71.7%
68.0%
52.8%
30.2%
65.8%
82.4%
85.6%
82.0%
77.5%
66.6%
64.8%
72.7%
67.7%
74.0%
69.8%
54.4%
Ratio
0.74
0.69
0.58
0.57
0.59
0.61
0.64
0.64
0.68
0.70
0.69
0.69
0.58
0.98
0.79
0.66
0.65
0.68
0.68
0.69
0.68
0.68
0.67
0.66
0.66
0.62
0.59
0.72
0.80
0.76
0.76
0.72
0.70
0.72
0.69
0.65
0.64
0.61
0.62
Difference
3.6%
15.7%
29.3%
31.4%
29.1%
26.1%
22.6%
20.3%
15.5%
12.7%
9.3%
5.9%
7.5%
0.5%
13.0%
25.9%
26.2%
23.3%
21.9%
20.4%
20.5%
17.9%
16.9%
13.9%
9.7%
10.4%
7.5%
15.7%
14.3%
17.7%
17.8%
20.2%
20.9%
18.9%
18.4%
19.2%
16.8%
14.6%
15.4%
by age-group and province. Ratios of coverage BIR=0 / coverage BIR=1 and difference coverage BIR=0 coverage BIR=1.
Age
Province group
Antwerp 15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
West15-19
Flanders 20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
East15-19
Flanders 20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
BIR=0
#smears/
3-year #women
coverage
ratio
14.6%
0.19
50.0%
0.80
70.9%
1.26
74.2%
1.35
72.0%
1.33
68.6%
1.25
63.7%
1.17
58.1%
1.09
50.2%
0.91
43.8%
0.78
28.4%
0.51
17.0%
0.29
15.8%
0.25
13.8%
0.18
48.8%
0.78
69.8%
1.24
70.9%
1.29
67.2%
1.24
64.2%
1.19
60.2%
1.13
54.3%
1.02
44.9%
0.83
38.7%
0.70
27.3%
0.48
17.1%
0.29
16.9%
0.27
14.2%
0.18
50.5%
0.81
69.7%
1.25
73.0%
1.37
70.2%
1.35
66.5%
1.27
61.1%
1.19
55.7%
1.12
46.6%
0.92
40.7%
0.80
29.2%
0.54
18.5%
0.33
19.3%
0.31
BIR=1
#smears/
Excess 3-year #women
use
coverage
ratio
30.6%
9.6%
0.12
60.4% 34.7%
0.53
77.2% 43.6%
0.69
82.1% 45.4%
0.74
84.7% 46.5%
0.74
82.1% 43.3%
0.70
83.3% 41.6%
0.69
87.1% 38.2%
0.59
82.0% 35.8%
0.58
77.8% 33.3%
0.53
80.4% 20.0%
0.34
73.5% 12.2%
0.20
59.6%
9.8%
0.14
28.2% 14.6%
0.18
59.7% 35.0%
0.55
77.4% 36.2%
0.62
81.8% 37.1%
0.59
84.1% 36.6%
0.56
85.7% 39.5%
0.63
87.1% 38.3%
0.62
88.2% 34.2%
0.56
85.4% 30.5%
0.50
80.3% 27.7%
0.45
75.7% 18.9%
0.31
71.6% 12.2%
0.19
58.3%
9.5%
0.13
28.3% 11.4%
0.14
59.9% 36.7%
0.57
79.7% 40.9%
0.65
87.5% 44.1%
0.71
91.8% 39.7%
0.64
91.8% 39.7%
0.67
94.5% 38.4%
0.64
100.4% 35.4%
0.58
98.6% 30.6%
0.53
96.6% 26.5%
0.46
85.6% 20.4%
0.35
78.6% 13.4%
0.22
60.6% 11.2%
0.16
Contrast 3-y
coverage
Excess
use
25.5%
54.2%
58.5%
61.8%
59.4%
60.9%
66.4%
55.1%
62.2%
59.9%
68.2%
62.8%
44.4%
22.6%
58.0%
72.5%
59.0%
52.5%
59.2%
61.3%
64.1%
62.6%
62.4%
64.7%
58.1%
39.5%
24.3%
54.1%
60.0%
60.1%
62.0%
67.8%
65.7%
64.8%
74.0%
75.1%
70.7%
63.5%
43.7%
Ratio
0.66
0.69
0.61
0.61
0.64
0.63
0.65
0.66
0.71
0.76
0.70
0.72
0.62
1.06
0.72
0.52
0.52
0.54
0.61
0.64
0.63
0.68
0.72
0.69
0.71
0.56
0.80
0.73
0.59
0.60
0.57
0.60
0.63
0.64
0.66
0.65
0.70
0.72
0.58
Difference
4.9%
15.3%
27.3%
28.8%
25.6%
25.3%
22.1%
19.9%
14.5%
10.5%
8.4%
4.8%
5.9%
-0.9%
13.8%
33.7%
33.9%
30.6%
24.8%
21.9%
20.1%
14.3%
10.9%
8.3%
4.9%
7.4%
2.8%
13.8%
28.8%
28.9%
30.4%
26.8%
22.7%
20.3%
15.9%
14.2%
8.8%
5.2%
8.2%
119
Age
Province group
Limburg 15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Flemish- 15-19
Brabant 20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Hainaut 15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
120
BIR=0
#smears/
3-year #women
ratio
coverage
12.9%
0.16
47.7%
0.72
67.9%
1.15
71.4%
1.23
66.0%
1.13
62.9%
1.09
59.2%
1.04
54.1%
0.98
47.5%
0.86
40.6%
0.71
30.1%
0.50
18.4%
0.30
15.0%
0.22
15.5%
0.20
51.9%
0.83
70.3%
1.24
74.9%
1.36
73.6%
1.37
70.4%
1.32
66.5%
1.27
61.3%
1.19
55.2%
1.07
48.6%
0.93
37.5%
0.70
25.0%
0.45
22.0%
0.37
21.9%
0.30
61.7%
1.07
74.6%
1.42
73.7%
1.40
70.5%
1.33
66.5%
1.25
63.8%
1.22
62.0%
1.22
53.2%
1.07
47.6%
0.95
37.6%
0.71
24.8%
0.45
23.2%
0.38
BIR=1
#smears/
ratio
use
coverage
23.9%
7.1%
0.08
50.7% 26.8%
0.40
69.5% 36.1%
0.57
72.6% 35.8%
0.56
71.8% 40.0%
0.59
73.1% 40.0%
0.62
76.4% 38.6%
0.60
81.4% 36.6%
0.58
82.0% 34.9%
0.59
75.0% 31.0%
0.51
67.1% 22.5%
0.36
63.0% 12.7%
0.19
46.6%
9.6%
0.13
30.4% 11.3%
0.15
60.5% 33.8%
0.52
76.8% 39.2%
0.63
81.2% 36.1%
0.60
86.3% 36.2%
0.56
88.0% 37.5%
0.61
90.7% 40.3%
0.64
93.6% 37.7%
0.62
93.9% 36.3%
0.62
91.7% 31.8%
0.54
86.2% 25.7%
0.45
79.6% 16.1%
0.27
66.7% 12.4%
0.19
38.1% 23.5%
0.32
73.4% 49.6%
0.94
90.8% 49.0%
0.90
90.0% 49.4%
0.86
88.8% 49.3%
0.84
88.1% 47.2%
0.80
92.0% 47.4%
0.82
97.3% 42.7%
0.72
100.4% 38.0%
0.68
99.3% 33.0%
0.61
88.9% 25.1%
0.44
82.1% 17.3%
0.29
64.1% 15.5%
0.23
Contrast 3-y
coverage
Excess
use
17.8%
47.8%
57.6%
57.7%
48.7%
55.1%
56.8%
59.4%
68.2%
64.2%
59.7%
51.1%
36.0%
30.2%
55.4%
60.6%
67.0%
53.8%
61.8%
59.9%
65.0%
71.4%
69.5%
74.3%
66.5%
50.3%
34.7%
90.3%
84.3%
74.7%
70.0%
69.1%
72.1%
69.5%
79.1%
84.6%
75.2%
68.4%
51.3%
Ratio
0.55
0.56
0.53
0.50
0.61
0.64
0.65
0.68
0.73
0.76
0.75
0.69
0.64
0.73
0.65
0.56
0.48
0.49
0.53
0.61
0.61
0.66
0.65
0.68
0.64
0.56
1.07
0.80
0.66
0.67
0.70
0.71
0.74
0.69
0.71
0.69
0.67
0.70
0.67
Difference
5.8%
21.0%
31.8%
35.5%
26.1%
22.9%
20.6%
17.5%
12.6%
9.6%
7.6%
5.7%
5.4%
4.2%
18.2%
31.1%
38.9%
37.4%
32.9%
26.2%
23.6%
18.9%
16.8%
11.8%
8.9%
9.6%
-1.5%
12.1%
25.6%
24.3%
21.2%
19.3%
16.3%
19.3%
15.3%
14.6%
12.5%
7.5%
7.7%
Age
Province group
Liège
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Luxem- 15-19
bourg
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Namur
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
BIR=0
#smears/
3-year #women
ratio
coverage
25.7%
0.36
65.2%
1.13
77.6%
1.46
77.3%
1.46
74.9%
1.43
72.0%
1.38
69.7%
1.35
66.2%
1.32
59.6%
1.18
53.7%
1.04
45.4%
0.84
33.1%
0.59
34.0%
0.56
21.0%
0.28
58.4%
0.97
75.9%
1.42
74.2%
1.35
69.7%
1.26
65.3%
1.20
62.7%
1.17
58.6%
1.13
50.3%
0.99
44.8%
0.83
33.9%
0.62
21.5%
0.37
17.8%
0.28
22.2%
0.30
59.6%
1.03
76.1%
1.44
74.9%
1.43
71.3%
1.34
68.0%
1.28
65.1%
1.26
62.3%
1.25
54.6%
1.09
47.5%
0.93
38.1%
0.71
25.0%
0.46
22.8%
0.39
BIR=1
#smears/
ratio
use
coverage
40.0% 24.4%
0.32
72.7% 51.7%
0.91
88.3% 57.3%
1.05
89.3% 54.5%
0.96
90.2% 53.8%
0.92
90.9% 52.0%
0.89
93.5% 48.4%
0.83
98.7% 47.1%
0.80
98.0% 42.5%
0.75
94.6% 37.5%
0.65
86.1% 31.6%
0.54
77.8% 23.3%
0.39
65.6% 21.4%
0.33
32.5% 18.2%
0.23
66.4% 34.1%
0.54
87.6% 22.4%
0.37
82.6% 24.9%
0.35
81.3% 37.6%
0.53
84.0% 36.1%
0.57
86.9% 39.0%
0.63
93.2% 34.6%
0.55
96.1% 28.7%
0.49
84.8% 25.2%
0.42
82.5% 21.7%
0.36
71.3% 12.4%
0.19
56.6% 12.3%
0.18
35.1% 21.7%
0.29
72.5% 50.5%
0.87
88.8% 45.7%
0.82
90.4% 40.4%
0.70
87.9% 43.0%
0.69
88.7% 40.4%
0.65
93.5% 40.8%
0.67
101.1% 39.8%
0.66
100.5% 34.4%
0.59
95.9% 31.5%
0.55
86.6% 25.3%
0.44
84.5% 17.0%
0.29
71.3% 14.0%
0.22
Contrast 3-y
coverage
Excess
use
32.7%
76.0%
82.8%
75.5%
71.5%
70.4%
71.6%
69.0%
75.5%
73.5%
69.5%
69.0%
55.7%
25.9%
59.6%
63.0%
41.8%
41.1%
57.1%
63.0%
57.4%
69.5%
65.3%
63.5%
50.0%
43.3%
32.0%
72.9%
80.5%
72.7%
61.3%
61.7%
64.0%
65.4%
72.0%
74.8%
74.9%
73.5%
55.4%
Ratio
0.95
0.79
0.74
0.71
0.72
0.72
0.69
0.71
0.71
0.70
0.70
0.70
0.63
0.87
0.58
0.30
0.34
0.54
0.55
0.62
0.59
0.57
0.56
0.64
0.57
0.69
0.98
0.85
0.60
0.54
0.60
0.59
0.63
0.64
0.63
0.66
0.66
0.68
0.62
Difference
1.4%
13.5%
20.3%
22.8%
21.1%
20.0%
21.3%
19.1%
17.1%
16.1%
13.7%
9.8%
12.6%
2.8%
24.3%
53.5%
49.3%
32.1%
29.1%
23.8%
23.9%
21.6%
19.6%
12.2%
9.2%
5.5%
0.5%
9.1%
30.4%
34.5%
28.4%
27.7%
24.3%
22.5%
20.3%
16.0%
12.8%
8.0%
8.8%
121
Age
Province group
Walloon- 15-19
Brabant 20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Brussels 15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
122
BIR=0
#smears/
3-year #women
ratio
coverage
25.6%
0.37
66.4%
1.24
77.9%
1.60
79.7%
1.62
79.9%
1.62
75.8%
1.54
73.4%
1.50
69.4%
1.46
63.2%
1.33
57.8%
1.20
48.3%
0.98
35.6%
0.69
33.9%
0.59
18.5%
0.26
55.9%
0.95
70.1%
1.29
74.8%
1.45
73.1%
1.43
71.1%
1.40
69.3%
1.38
67.5%
1.40
59.8%
1.25
55.2%
1.16
46.8%
0.95
37.1%
0.72
40.2%
0.69
BIR=1
#smears/
ratio
use
coverage
44.0% 13.7%
0.17
87.2% 39.6%
0.66
106.0% 32.8%
0.57
103.0% 44.0%
0.70
102.1% 44.6%
0.77
103.1% 44.3%
0.75
104.7% 42.0%
0.70
110.0% 42.0%
0.73
110.4% 39.8%
0.72
107.8% 31.6%
0.56
103.4% 29.9%
0.50
92.6% 19.3%
0.32
72.7% 16.8%
0.25
39.8% 10.8%
0.14
70.1% 39.8%
0.67
84.2% 55.2%
1.02
93.8% 56.4%
1.06
96.0% 54.8%
1.01
97.2% 50.4%
0.90
99.4% 48.3%
0.81
107.5% 48.2%
0.80
108.6% 41.2%
0.71
109.7% 35.8%
0.60
102.1% 29.8%
0.52
93.4% 22.4%
0.38
72.1% 24.8%
0.38
Contrast 3-y
coverage
Excess
use
22.9%
66.4%
74.7%
58.5%
72.4%
70.2%
66.2%
73.9%
81.1%
77.6%
67.6%
65.4%
49.2%
31.2%
67.3%
84.1%
87.6%
83.5%
78.8%
67.2%
65.7%
73.3%
68.3%
74.5%
70.1%
54.4%
Ratio
0.54
0.60
0.42
0.55
0.56
0.58
0.57
0.60
0.63
0.55
0.62
0.54
0.49
0.59
0.71
0.79
0.75
0.75
0.71
0.70
0.71
0.69
0.65
0.64
0.60
0.62
Difference
11.8%
26.8%
45.1%
35.8%
35.3%
31.5%
31.4%
27.5%
23.3%
26.2%
18.4%
16.3%
17.1%
7.6%
16.1%
14.8%
18.4%
18.3%
20.6%
21.1%
19.3%
18.6%
19.4%
17.0%
14.7%
15.4%
12.6. Profession of smear takers, by province
Table 48. Proportion of cervical cell samples taken by general practitioners, by calendar year and
province (Flemish Region, 1996-2000 and 2002-2006).
Year
1996
1997
1998
1999
2000
2002
2003
2004
2005
2006
Antwerp
29.2%
28.4%
26.7%
24.7%
24.2%
21.7%
19.6%
19.4%
18.5%
17.2%
W-Flanders
22.4%
22.2%
19.3%
19.0%
16.0%
14.3%
13.2%
12.4%
11.9%
11.1%
E-Flanders
20.8%
19.6%
18.6%
17.1%
15.2%
13.2%
12.7%
11.9%
11.1%
10.2%
Limburg
33.8%
30.0%
27.4%
26.0%
24.7%
22.9%
22.2%
20.3%
18.6%
18.0%
Flemish-Brabant
23.8%
24.1%
22.4%
21.4%
20.4%
18.5%
18.1%
17.2%
16.5%
16.0%
Table 49. Proportion of cervical cell samples taken by general practitioners, by calendar year
(Brussels, 1996-2000 and 2002-2006).
Year
1996
1997
1998
1999
2000
2002
2003
2004
2005
2006
Brussels
10.2%
9.6%
9.0%
8.5%
8.3%
7.4%
7.0%
6.9%
6.8%
6.8%
Table 50. Proportion of cervical cell samples taken by general practitioners, by calendar year and
province (Walloon Region, 1996-2000 and 2002-2006).
Year
1996
1997
1998
1999
2000
2002
2003
2004
2005
2006
Hainaut
3.3%
3.0%
2.7%
2.7%
2.5%
1.7%
1.5%
1.3%
1.2%
1.1%
Liège
3.1%
3.2%
2.5%
2.4%
2.2%
1.4%
1.3%
1.2%
1.2%
1.1%
Luxembourg
8.3%
8.2%
7.4%
6.9%
6.8%
3.1%
2.9%
2.5%
2.3%
2.0%
Namur
5.5%
4.8%
4.5%
4.3%
3.7%
2.8%
2.6%
2.5%
2.4%
2.2%
Walloon-Brabant
8.5%
7.8%
7.2%
6.8%
6.1%
5.1%
4.4%
4.0%
3.7%
3.9%
123
12.7. Interval between successive Pap smears, by age group
Table 51. Interval between successive Pap smear collections (in months), by age group (Belgium,
2002-06).
Age group (years)
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Minimum
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25th
%ile
4
9
10
10
11
11
11
11
11
11
12
11
11
11
Median
10
12
13
13
13
13
13
13
13
13
13
13
13
13
Mean
10.3
12.8
14.6
15.1
15.4
15.5
15.6
15.5
15.2
15.3
15.5
15.3
15.2
15.2
75th
%ile
13
15
18
19
19
19
19
18
18
18
18
18
18
19
Maximum
45
59
59
59
59
59
59
59
59
59
59
59
59
59
Table 52. Interval between successive Pap smear collections (in months), by province (Belgium,
2002-06).
Province
Censored
Unknown
Antwerp
West-Flanders
East-Flanders
Hainaut
Liège
Limburg
Luxembourg
Namur
Brussels
Flemish-Brabant
Walloon-Brabant
124
Minimum
0
0
0
0
0
0
0
0
0
0
0
0
0
25th
%ile
7
10
11
11
11
11
11
11
11
11
10
11
11
Median
12
13
13
13
13
13
13
14
14
13
13
13
13
Mean
13.3
14.3
15.9
15.6
15.1
15.2
15.4
16.3
15.7
15.3
14.3
15.5
14.6
75th
%ile
17
17
19
19
18
18
19
20
19
19
17
19
17
Maximum
59
57
59
59
59
59
59
59
59
59
59
59
59
12.8. Data files and statistical syntaxis files
-
-
-
directory: :\Intermut\2001_6\
mother file: cervixresult.sas7bdat, translated into a Stata file using
StatTransfer.
create do files:
o readsasfile.do->intermut0.dta.
o intermut_read0.do (exploratory, overruled by *read1.do)
o intermut_read1.do->intermut1.dta, where a ranked identificator=num is
created and geographical labels are added and variables renamed
according to intermut1996_2000., generates subfile intermut2.dta with
only the Pap smear interpretations
pap smear interpretation:
o 1 year coverage: an_1ycov.do, Intermut2001_6.xls (sheet 1ycov)
o 3-year coverage: 3yearCov2002_2004.do, 3yearCov2004_2006.do,
ntermut2001_6.xls (sheet 3cov)
o 5 year coverage: 5yearCov.do, ntermut2001_6.xls (sheet 5ycov)
profession of smear takers: takingpap.do, Intermut2001_6.xls (sheet
SmearTaking)
interval between successive Pap smear collections: interv.do,
Intermut2001_6.xls (sheet Interv)
colposcopy and cervical biopsies: colpo.do; Intermut2001_6.xls (sheet Colpo)
conisation: conus.do & conus2.do; Intermut2001_6.xls (sheet Colpo)
hysterectomy: hyster.do; hyster.xls, ; Intermut2001_6.xls (sheet Hyster)
screening in hysterectomised women: cyt_hyst.do; Intermut2001_6.xls (sheet
Cyt_hyst)
-
Comparison with health interview survey:
o Directory: \Intermut\2001_6\HIS2004
o Command files: his1.do
o Tables in Intermut2001_6.xls (sheet HISIMA.XLS)
-
Data from RIVIZ: \xls\cervix\cvxriziv.xls
o Intermut2001_6.xls (sheet RIZIVIMA.XLS)
-
Data from Limburg cytology registry: D:\DATA\an\casecontrol\5aug2008
o ana_cyto7.do
125

analysis of individual health insurance data pertaining to pap

Transcription

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