The Cox model is better than the Fine and Gray model when estimating relative revision risks from arthroplasty register data

Abstract

Background and purpose — Analysis of the revision-free survival of knee and hip prostheses has traditionally been performed using Kaplan–Meier analysis and Cox regression. The competing risk problem that is related to patients who die during follow-up has recently been increasingly discussed, not least with regard to the problem of choosing a suitable statistical method for the analysis. We compared the results from analyses of Cox models and Fine and Gray models. Methods — We used data simulation based on parameter estimates from the Swedish Knee Arthroplasty Register and assessed hypothetical effects of the studied risk factors. Results — The Cox model provided more adequate results. Interpretation — The parameter estimates from the Fine and Gray model can be misleading if interpreted in terms of relative risk.