Literature DB >> 19773581

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

Björn Stollenwerk1, Andreas Gerber, Karl W Lauterbach, Uwe Siebert.   

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.

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Year:  2009        PMID: 19773581     DOI: 10.1177/0272989X09331810

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  6 in total

1.  Cost-of-illness studies based on massive data: a prevalence-based, top-down regression approach.

Authors:  Björn Stollenwerk; Thomas Welchowski; Matthias Vogl; Stephanie Stock
Journal:  Eur J Health Econ       Date:  2015-02-04

2.  Accounting for increased non-target-disease-specific mortality in decision-analytic screening models for economic evaluation.

Authors:  Björn Stollenwerk; Afschin Gandjour; Markus Lüngen; Uwe Siebert
Journal:  Eur J Health Econ       Date:  2012-12-30

3.  Acceptability of predictive testing for ischemic heart disease in those with a family history and the impact of results on behavioural intention and behaviour change: a systematic review.

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

4.  The association between health system development and the burden of cardiovascular disease: an analysis of WHO country profiles.

Authors:  Yanmei Liu; Koustuv Dalal; Björn Stollenwerk
Journal:  PLoS One       Date:  2013-04-18       Impact factor: 3.240

5.  The effectiveness of the cardiovascular disease prevention programme 'KardioPro' initiated by a German sickness fund: a time-to-event analysis of routine data.

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

6.  Systematic Review of Validity Assessments of Framingham Risk Score Results in Health Economic Modelling of Lipid-Modifying Therapies in Europe.

Authors:  Jonas Hermansson; Thomas Kahan
Journal:  Pharmacoeconomics       Date:  2018-02       Impact factor: 4.981

  6 in total

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