Different competing risks models for different questions may give similar results in arthroplasty registers in the presence of few events.

ABSTRACT: Background and purpose - In arthroplasty registry studies, the analysis of time to revision is complicated by the competing risk of death. There are no clear guidelines for the choice between the 2 main adjusted analysis methods, cause-specific Cox and Fine-Gray regression, for orthopedic data. We investigated whether there are benefits, such as insight into different aspects of progression to revision, to using either 1 or both regression methods in arthroplasty registry studies in general, and specifically when the length of follow-up is short relative to the expected survival of the implants. Patients and methods - Cause-specific Cox regression and Fine-Gray regression were performed on total hip (138,234 hips, 124,560 patients) and knee (139,070 knees, 125,213 patients) replacement dat

SUBMITTER: Van Der Pas S 

PROVIDER: S-EPMC5901510 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature