| Literature DB >> 35231928 |
Cristoforo Simonetto, Margit Heier, Annette Peters, Jan Christian Kaiser, Susanne Rospleszcz.
Abstract
Mathematical models are able to reflect biological processes and to capture epidemiologic data. Thus, they may help elucidate roles of risk factors in disease progression. We propose to account for smoking, hypertension, and dyslipidemia in a previously published process-oriented model that describes the development of atherosclerotic lesions resulting in myocardial infarction (MI). The model is sex-specific and incorporates individual heterogeneity. It was applied to population-based individual risk factors and MI rates (Cooperative Health Research in the Region of Augsburg (KORA) study) together with subclinical atherosclerotic lesion data (Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study). Different model variants were evaluated, testing the association of risk factors with different disease processes. Best fits were obtained for smoking affecting a late-stage disease process, suggesting a thrombogenic role. Hypertension was mainly related to complicated, vulnerable lesions. Dyslipidemia was consistent with increasing the number of initial lesions. By accounting for heterogeneity, individual hazard ratios differ from the population average. The mean individual hazard ratio for smoking was twice the population-based hazard ratio for men and even more for women. Atherosclerotic lesion progression and MI incidence data can be related in a mathematical model to illuminate how risk factors affect different phases of this pathological process.Entities:
Keywords: atherosclerosis; biological models; cardiovascular risk factors; computer simulation; myocardial infarction; survival analysis
Mesh:
Year: 2022 PMID: 35231928 PMCID: PMC9535448 DOI: 10.1093/aje/kwac038
Source DB: PubMed Journal: Am J Epidemiol ISSN: 0002-9262 Impact factor: 5.363