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BMC Medicine
Published in: BMC Medicine 1/2014

Open Access 01-12-2014 | Research article

Sex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysis

Authors: Hanna M van Loo, Edwin R van den Heuvel, Robert A Schoevers, Matteo Anselmino, Robert M Carney, Johan Denollet, Frank Doyle, Kenneth E Freedland, Sherry L Grace, Seyed H Hosseini, Kapil Parakh, Louise Pilote, Chiara Rafanelli, Annelieke M Roest, Hiroshi Sato, Richard P Steeds, Ronald C Kessler, Peter de Jonge

Published in: BMC Medicine | Issue 1/2014

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Abstract

Background

Although a number of risk factors are known to predict mortality within the first years after myocardial infarction, little is known about interactions between risk factors, whereas these could contribute to accurate differentiation of patients with higher and lower risk for mortality. This study explored the effect of interactions of risk factors on all-cause mortality in patients with myocardial infarction based on individual patient data meta-analysis.

Methods

Prospective data for 10,512 patients hospitalized for myocardial infarction were derived from 16 observational studies (MINDMAPS). Baseline measures included a broad set of risk factors for mortality such as age, sex, heart failure, diabetes, depression, and smoking. All two-way and three-way interactions of these risk factors were included in Lasso regression analyses to predict time-to-event related all-cause mortality. The effect of selected interactions was investigated with multilevel Cox regression models.

Results

Lasso regression selected five two-way interactions, of which four included sex. The addition of these interactions to multilevel Cox models suggested differential risk patterns for males and females. Younger women (age <50) had a higher risk for all-cause mortality than men in the same age group (HR 0.7 vs. 0.4), while men had a higher risk than women if they had depression (HR 1.4 vs. 1.1) or a low left ventricular ejection fraction (HR 1.7 vs. 1.3). Predictive accuracy of the Cox model was better for men than for women (area under the curves: 0.770 vs. 0.754).

Conclusions

Interactions of well-known risk factors for all-cause mortality after myocardial infarction suggested important sex differences. This study gives rise to a further exploration of prediction models to improve risk assessment for men and women after myocardial infarction.
Appendix
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Metadata
Title
Sex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysis
Authors
Hanna M van Loo
Edwin R van den Heuvel
Robert A Schoevers
Matteo Anselmino
Robert M Carney
Johan Denollet
Frank Doyle
Kenneth E Freedland
Sherry L Grace
Seyed H Hosseini
Kapil Parakh
Louise Pilote
Chiara Rafanelli
Annelieke M Roest
Hiroshi Sato
Richard P Steeds
Ronald C Kessler
Peter de Jonge
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2014
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-014-0242-y

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