Kaplan-Meier Survival Analysis Overestimates Cumulative Incidence of Health-related Events in the Presence of Competing Risks: A Meta-analysis

Publication date: Available online 16 October 2017
Source:Journal of Clinical Epidemiology
Author(s): Sarah Lacny, Todd Wilson, Fiona Clement, Derek J. Roberts, Peter Faris, William A. Ghali, Deborah A. Marshall
ObjectiveKaplan-Meier survival analysis may overestimate cumulative incidence in competing risks (CR) settings. The clinical significance of this overestimation has been questioned and CR methods are infrequently used. This meta-analysis compares the Kaplan-Meier method to the cumulative incidence function (CIF), a CR method.Study Design and SettingWe searched MEDLINE, EMBASE, BIOSIS Previews, Web of Science (1992-2016), and article bibliographies for studies estimating cumulative incidence using the Kaplan-Meier method and CIF. For studies with sufficient data, we calculated pooled risk ratios (RRs) comparing Kaplan-Meier and CIF estimates using DerSimonian and Laird random effects models. We performed stratified meta-analyses by clinical area, rate of CRs, and follow-up time.ResultsOf 2,192 identified abstracts, we included 77 studies in the systematic review. Fifty-five studies were meta-analyzed. The pooled RR demonstrated the Kaplan-Meier estimate was 1.41 (95% CI 1.36-1.47) times higher than the CIF. Overestimation was highest among studies with high rates of CRs (RR=2.36 [95% CI 1.79-3.12]), and studies related to hepatology (RR=2.60 [95% CI 2.12-3.19]) and obstetrics and gynecology (RR=1.84 [95% CI 1.52-2.23]).ConclusionsThe Kaplan-Meier method overestimated the cumulative incidence across ten clinical areas. Competing risks should be considered to ensure accurate results inform clinical and policy decisions.



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