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.
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.
Authors: Imogen Wells; Gwenda Simons; Clare Davenport; Christian D Mallen; Karim Raza; Marie Falahee Journal: BMC Public Health Date: 2022-09-15 Impact factor: 4.135
Authors: Sabine Witt; Reiner Leidl; Christian Becker; Rolf Holle; Michael Block; Johannes Brachmann; Sigmund Silber; Björn Stollenwerk Journal: PLoS One Date: 2014-12-08 Impact factor: 3.240