Speaker
Speaker: Marianne Gillam, PhD student, School of Population Health
and Clinical Practice, University of Adelaide, Adelaide.
Abstract
Arthroplasty registry data are traditionally analysed using standard survival methods, that is, Kaplan-Meier survival curves and Cox Proportional Hazards models. The outcome of interest is the time from the primary procedure until revision of the prosthesis which is a crude measure of success or otherwise of the arthroplasty. In the presence of a high incidence of a competing risk such as death, different methods and interpretation are required in the analysis.
In this talk I will present the results of two studies1-2 where we applied competing risks methods to data from AOA NJRR (the Australian Orthopaedic Association National Joint Replacement Registry) and compared the results to those obtained using standard survival methods.
Although competing risks methods are well known in the statistical community, they are infrequently used in orthopaedic research. This may be due to a lack of awareness of the limitations and of the interpretational difficulties of the Kaplan Meier and Cox proportional hazards methods in the presence of competing risks.
References
1 Gillam MH, Ryan P, Graves SE, Miller LN, de Steiger RN, Salter A. Competing risks survival analysis applied to data from the Australian Orthopaedic Association National Joint Replacement Registry. Acta Orthop 2010;81(5):548-55.
2 Gillam MH, Salter A, Ryan P, Graves SE. Different competing risks models applied to data from the Australian Orthopaedic Association National Joint Replacement Registry. Acta Orthop 2011;82(5):513-20.