Are competing risks models appropriate to describe implant failure?

Adrian Sayers*, Jonathan T. Evans, Michael R. Whitehouse, Ashley W. Blom

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

43 Citations (Scopus)
297 Downloads (Pure)

Abstract

Background and purpose — The use of competing risks models is widely advocated in the arthroplasty literature due to a perceived bias in comparison of simple Kaplan–Meier estimates. Proponents of competing risk models in the arthroplasty literature appear to be unaware of the subtle but important differences in interpretation of net and crude failure estimated by competing risk and Kaplan–Meier methods respectively. Methods — Using a simple simulation we illustrate the differences between competing risks and Kaplan–Meier methods. Results — Competing risk and Kaplan–Meier methods estimate different survival quantities, i.e., crude and net failure respectively. Estimates of crude failure estimated using competing risk methods will be less than net failure as estimated using Kaplan–Meier methods. Interpretation — Kaplan–Meier methods are appropriate for describing implant failure, whereas crude survival estimated using competing risk methods estimates the risk of surgical revision as it depends on both implant failure and mortality. Both competing risk models and Kaplan–Meier methods are useful in arthroplasty, and both provide unbiased estimates of crude and net failure in the absence of any confounding or selection respectively. Surgeons and researchers should carefully consider whether the use of competing risks is always justified. Lower estimates of failure from competing risk models may be misleading to surgeons who are attempting to select the best implants with the lowest failure rates for their patients.

Original languageEnglish
Number of pages3
JournalActa Orthopaedica
Early online date9 Mar 2018
DOIs
Publication statusE-pub ahead of print - 9 Mar 2018

Structured keywords

  • Centre for Surgical Research

Keywords

  • Journal Article

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