Parametric conditional frailty models for recurrent cardiovascular events in the lipid study

Cui, Jisheng, Forbes, Andrew, Kirby, Adrienne, Marshner, Ian, Simes, John, West, Malcolm and Tonkin, Andrew 2008, Parametric conditional frailty models for recurrent cardiovascular events in the lipid study, Clinical trials, vol. 5, no. 6, pp. 565-574, doi: 10.1177/1740774508098464.

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Title Parametric conditional frailty models for recurrent cardiovascular events in the lipid study
Author(s) Cui, Jisheng
Forbes, Andrew
Kirby, Adrienne
Marshner, Ian
Simes, John
West, Malcolm
Tonkin, Andrew
Journal name Clinical trials
Volume number 5
Issue number 6
Start page 565
End page 574
Publisher Sage Science Press (UK)
Place of publication London, U.K.
Publication date 2008
ISSN 1740-7745
Summary Background Analysis of recurrent event data is frequently needed in clinical and epidemiological studies. An important issue in such analysis is how to account for the dependence of the events in an individual and any unobserved heterogeneity of the event propensity across individuals.Methods We applied a number of conditional frailty and nonfrailty models in an analysis involving recurrent myocardial infarction events in the Long-Term Intervention with Pravastatin in Ischaemic Disease study. A multiple variable risk prediction model was developed for both males and females. Results A Weibull model with a gamma frailty term fitted the data better than other frailty models for each gender. Among nonfrailty models the stratified survival model fitted the data best for each gender. The relative risk estimated by the elapsed time model was close to that estimated by the gap time model. We found that a cholesterol-lowering drug, pravastatin (the intervention being tested in the trial) had significant protective effect against the occurrence of myocardial infarction in men (HR¼0.71, 95% CI0.60–0.83). However, the treatment effect was not significant in women due to smaller sample size (HR¼0.75, 95% CI 0.51–1.10). There were no significant interactions between the treatment effect and each recurrent MI event (p¼0.24 for men and p¼0.55 for women). The risk of developing an MI event for a male who had an MI event during follow-up was about 3.4 (95% CI 2.6–4.4) times the risk compared with those who did not have an MI event. The corresponding relative risk for a female was about 7.8 (95% CI 4.4–13.6). Limitations The number of female patients was relatively small compared with their male counterparts, which may result in low statistical power to find real differences in the effect of treatment and other potential risk factors.Conclusions The conditional frailty model suggested that after accounting for all the risk factors in the model, there was still unmeasured heterogeneity of the risk for myocardial infarction, indicating the effect of subject-specific risk factors. These risk prediction models can be used to classify cardiovascular disease patients into different risk categories and may be useful for the most effective targeting of preventive therapies for cardiovascular disease.
Language eng
DOI 10.1177/1740774508098464
Field of Research 111706 Epidemiology
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2008, Society for Clinical Trials
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