Abstract
BackgroundTraditional methods for analyzing clinical and epidemiological cohort study data have been focused on the first occurrence of a health outcome. However, in many situations, recurrent event data are frequently observed. It is inefficient to use methods for the analysis of first events to analyse recurrent event data.MethodsWe applied several semi-parametric proportional hazards models to analyze the risk of recurrent myocardial infarction (MI) events based on data from a very large randomized placebo-controlled trial of cholesterol-lowering drug. The backward selection procedure was used to select the significant risk factors in a model. The best fitting model was selected using the log-likelihood ratio test, Akaike Information and Bayesian Information Criteria.ResultsA total of 8557 persons were included in the LIPID study. Risk factors such as age, smoking status, total cholesterol and high density lipoprotein cholesterol levels, qualifying event for the acute coronary syndrome, revascularization, history of stroke or diabetes, angina grade and treatment with pravastatin were significant for development of both first and subsequent MI events. No significant difference was found for the effects of these risk factors between the first and subsequent MI events. The significant risk factors selected in this study were the same as those selected by the parametric conditional frailty model. Estimates of the relative risks and 95% confidence intervals were also similar between these two methods.ConclusionsOur study shows the usefulness and convenience of the semi-parametric proportional hazards models for the analysis of recurrent event data, especially in estimation of regression coefficients and cumulative risks.
Highlights
Traditional methods for analyzing clinical and epidemiological cohort study data have been focused on the first occurrence of a health outcome
After the Follow-up in the Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID) Study Table 1 shows the number of myocardial infarction (MI) events and the outcome status of participants at the end of the study
A total of 870 MI events occurred in 745 patients during follow-up, of whom 313 had been randomized to receive pravastatin and 432 to receive placebo
Summary
Traditional methods for analyzing clinical and epidemiological cohort study data have been focused on the first occurrence of a health outcome. Many clinical and epidemiological cohort studies involve health outcomes that a participant of the study can experience several times during the follow-up period. Such outcomes are often termed recurrent or repeated events [1,2]. Traditional statistical methods for the analysis of cohort study data have been focused on the first occurrence of an outcome [5]. An individual may be prone to develop more recurrent events or the time interval between these events may be shorter than others in the study depending on the characteristics of the individual. Updated analytical methods are needed to account for the dependence of the repeated measurements in a person during follow-up study
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