The European Journal of Public Health Advance Access originally published online on February 9, 2006
The European Journal of Public Health 2006 16(2):185-192; doi:10.1093/eurpub/cki163
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Mental Health |
The German Cervical Cancer Screening Model: development and validation of a decision-analytic model for cervical cancer screening in Germany
Uwe Siebert1,2,3,4, Gaby Sroczynski1,2,3,4, Peter Hillemanns5, Jutta Engel6, Roland Stabenow7, Christa Stegmaier8, Kerstin Voigt2, Bernhard Gibis8, Dieter Hölzel9 and Sue J. Goldie2
1 Department of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University of Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
2 Harvard Center for Risk Analysis, Harvard School of Public Health, Boston, MA, USA
3 Institute for Technology Assessment, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
4 Program on Health Technology Assessment and Decision Sciences, Institute of Medical Informatics, Biostatistics, and Epidemiology, Ludwig-Maximilians-University Munich, Germany
5 Department of Obstetrics and Gynecology, Friedrich-Schiller University of Jena, Jena, Germany
6 Munich Cancer Registry of the Munich Comprehensive Cancer Centre, Ludwig-Maximilians-University and Technical University of Munich, Munich, Germany
7 Common Cancer Registry of the Federal States Berlin/Brandenburg/Mecklenburg-Vorpommern/Sachsen-Anhalt/Sachsen/Thüringen, Berlin, Germany
8 Saarland Cancer Registry, Saarbrücken, Germany
9 National Department for Health Care Quality, National Association of Statutory Health Insurance Physicians, Berlin, Germany
Correspondence: Uwe Siebert, MD, MSc, MPH, ScD, Department of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University of Health Sciences, Medical Informatics and Technology, Hall i.T., Austria, Eduard Wallnöfer-Zentrum I, A-6060 Hall i.T., tel.: +43 50 8648 3930, fax: 43 50 8648 673931, Email: uwe.siebert{at}umit.at
Background: We sought to develop and validate a decision-analytic model for the natural history of cervical cancer for the German health care context and to apply it to cervical cancer screening. Methods: We developed a Markov model for the natural history of cervical cancer and cervical cancer screening in the German health care context. The model reflects current German practice standards for screening, diagnostic follow-up and treatment regarding cervical cancer and its precursors. Data for disease progression and cervical cancer survival were obtained from the literature and German cancer registries. Accuracy of Papanicolaou (Pap) testing was based on meta-analyses. We performed internal and external model validation using observed epidemiological data for unscreened women from different German cancer registries. The model predicts life expectancy, incidence of detected cervical cancer cases, lifetime cervical cancer risks and mortality. Results: The model predicted a lifetime cervical cancer risk of 3.0% and a lifetime cervical cancer mortality of 1.0%, with a peak cancer incidence of 84/100 000 at age 51 years. These results were similar to observed data from German cancer registries, German literature data and results from other international models. Based on our model, annual Pap screening could prevent 98.7% of diagnosed cancer cases and 99.6% of deaths due to cervical cancer in women completely adherent to screening and compliant to treatment. Extending the screening interval from 1 year to 2, 3 or 5 years resulted in reduced screening effectiveness. Conclusions: This model provides a tool for evaluating the long-term effectiveness of different cervical cancer screening tests and strategies.
Keywords: cervical cancer, decision analysis, Markov model, screening