Kaplan-Meier Survival Analysis Overestimates the Risk of Revision Arthroplasty: A Meta-analysis

Abstract

Background: Although Kaplan-Meier survival analysis is commonly used to estimate the cumulative incidence of revision after joint arthroplasty, it theoretically overestimates the risk of revision in the presence of competing risks (such as death). Because the magnitude of overestimation is not well documented, the potential associated impact on clinical and policy decision-making remains unknown.

Questions/purposes: We performed a meta-analysis to answer the following questions: (1) To what extent does the Kaplan-Meier method overestimate the cumulative incidence of revision after joint replacement compared with alternative competing-risks methods? (2) Is the extent of overestimation influenced by followup time or rate of competing risks?

Methods: We searched Ovid MEDLINE, EMBASE, BIOSIS Previews, and Web of Science (1946, 1980, 1980, and 1899, respectively, to October 26, 2013) and included article bibliographies for studies comparing estimated cumulative incidence of revision after hip or knee arthroplasty obtained using both Kaplan-Meier and competing-risks methods. We excluded conference abstracts, unpublished studies, or studies using simulated data sets. Two reviewers independently extracted data and evaluated the quality of reporting of the included studies. Among 1160 abstracts identified, six studies were included in our meta-analysis. The principal reason for the steep attrition (1160 to six) was that the initial search was for studies in any clinical area that compared the cumulative incidence estimated using the Kaplan-Meier versus competing-risks methods for any event (not just the cumulative incidence of hip or knee revision); we did this to minimize the likelihood of missing any relevant studies. We calculated risk ratios (RRs) comparing the cumulative incidence estimated using the Kaplan-Meier method with the competing-risks method for each study and used DerSimonian and Laird random effects models to pool these RRs. Heterogeneity was explored using stratified meta-analyses and metaregression.

Results: The pooled cumulative incidence of revision after hip or knee arthroplasty obtained using the Kaplan-Meier method was 1.55 times higher (95% confidence interval, 1.43-1.68; p < 0.001) than that obtained using the competing-risks method. Longer followup times and higher proportions of competing risks were not associated with increases in the amount of overestimation of revision risk by the Kaplan-Meier method (all p > 0.10). This may be due to the small number of studies that met the inclusion criteria and conservative variance approximation.

Conclusions: The Kaplan-Meier method overestimates risk of revision after hip or knee arthroplasty in populations where competing risks (such as death) might preclude the occurrence of the event of interest (revision). Competing-risks methods should be used to more accurately estimate the cumulative incidence of revision when the goal is to plan healthcare services and resource allocation for revisions.

Fig. 1

The flow of articles through the systematic review process is illustrated using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram.

Fig. 2A–B

Forest plots of RRs compare the cumulative incidence of revision after hip or knee arthroplasty obtained using the Kaplan-Meier method versus competing-risks method for seven strata (six studies*) containing (A) the highest ratio of competing events to events of interest; and (B) the largest number of revisions. *Gillam et al. [17] estimated the cumulative incidence of revision after THA for three nonmutually exclusive subsets of data. The subset with the largest number of events of interest included two mutually exclusive strata: patients with osteoarthritis aged < 70 years and patients with osteoarthritis aged ≥ 70 years. The subset with the highest rate of competing risks included two mutually exclusive strata (cementless Austin Moore prostheses and cemented Thompson prostheses). KM = Kaplan-Meier; CR = competing risks.