Abstract

There is large inter-individual heterogeneity in risk of coronary heart disease (CHD). Risk factors traditionally used in primary risk assessment only partially explain this heterogeneity. Residual, unobserved heterogeneity leads to age-related attenuation of hazard rates and underestimation of hazard ratios. Its magnitude is unknown. Therefore, we aimed to estimate a lower and an approximate upper bound. Heterogeneity was parametrized by a log-normal distribution with shape parameter σ. Analysis was based on published data. From concordance indices of studies including traditional risk factors and additional diagnostic imaging data, we calculated the part of heterogeneity explained by imaging data. For traditional risk assessment, this part typically remains unexplained, thus constituting a lower bound on unobserved heterogeneity. Next, the potential impact of heterogeneity on CHD hazard rates in several large countries was investigated. CHD rates increase with age but the increase attenuates with age. Presuming this attenuation to be largely caused by heterogeneity, an approximate upper bound on σ was derived. Taking together both bounds, unobserved heterogeneity in studies without imaging information can be described by a shape parameter in the range σ = 1–2. It substantially contributes to observed age-dependences of hazard ratios and may lead to underestimation of hazard ratios by a factor of about two. Therefore, analysis of studies for primary CHD risk assessment should account for unobserved heterogeneity.

Details

Title
Heterogeneity in coronary heart disease risk
Author
Simonetto, Cristoforo 1 ; Rospleszcz, Susanne 2 ; Kaiser, Jan Christian 1 ; Furukawa, Kyoji 3 

 Helmholtz Zentrum München German Research Center for Environmental Health (GmbH), Institute of Radiation Medicine, Neuherberg, Germany (GRID:grid.4567.0) (ISNI:0000 0004 0483 2525) 
 Helmholtz Zentrum München German Research Center for Environmental Health (GmbH), Institute of Epidemiology, Neuherberg, Germany (GRID:grid.4567.0) (ISNI:0000 0004 0483 2525); Ludwig-Maximilians-Universität München, Institute for Medical Information Processing, Biometry and Epidemiology, Munich, Germany (GRID:grid.5252.0) (ISNI:0000 0004 1936 973X); Partner Site Munich Heart Alliance, German Center for Cardiovascular Disease (DZHK), Munich, Germany (GRID:grid.452396.f) (ISNI:0000 0004 5937 5237) 
 Kurume University, Biostatistics Center, Fukuoka, Japan (GRID:grid.410781.b) (ISNI:0000 0001 0706 0776) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2677227236
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.