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The German Coronary Artery Disease Risk Screening Model: Development, Validation, and Application of a Decision-Analytic Model for Coronary Artery Disease Prevention with StatinsHelmholtz Zentrum München (GmbH), Institute of Health Economics and Health Care Management, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany, bjoern.stollenwerk{at}helmholtz-muenchen.de
Background. Coronary artery disease (CAD) is a major cause of death in industrial countries, leading to high health-related costs and decreased quality of life. Objective. To develop and validate a decision-analytic model for CAD risk screening in Germany (German Coronary Artery Disease Screening Model). Design. Markov model. Target Population. Age- and gender-specific cohorts of the German population. Data Sources. Mortality rates posted by the German Federal Statistical Office, the German Health Survey, social health insurance institutions, the MONICA Augsburg study, and the literature. Time Horizon. Lifetime. Interventions. CAD risk screening for high-risk individuals using Framingham risk equation and use of statins as the primary preventive measure, compared with a setting without screening. Outcome Measures. Life-years (LY) gained, quality-adjusted life-years (QALYs) gained. Results. The model-based CAD incidence corresponds well with empirical data from the MONICA Augsburg study. Health outcomes depend on the screening threshold (cutoff value of Framingham 10-year risk) and on the age and gender of the cohort screened (0.03 to 0.26 LYs and 0.06 to 0.42 QALYs gained per person screened in cohorts of 50- and 60-year-old men and women, respectively). Conclusions. The model provides a valid tool for evaluating the long-term effectiveness of CAD risk screening in Germany. Using statins as a primary prevention intervention for CAD in high-risk individuals identified by screening could improve the long-term health of the German population.
Key Words: coronary artery disease statins screening Markov model Germany.
This version was published on September
1, 2009 Medical Decision Making, Vol. 29, No. 5,
619-633 (2009) |
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