The German Coronary Artery Disease Risk Screening Model: development, validation, and application of a decision-analytic model for coronary artery disease prevention with statins

Abstract

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.