Aims To develop and validate patient-centred algorithms that estimate individual risk of death over the first year after elective joint arthroplasty surgery for osteoarthritis. Methods A total of 763,213 hip and knee joint arthroplasty episodes recorded in the National Joint Registry for England and Wales (NJR) and 105,407 episodes from the Norwegian Arthroplasty Register were used to model individual mortality risk over the first year after surgery using flexible parametric survival regression. Results The one-year mortality rates in the NJR were 10.8 and 8.9 per 1,000 patient-years after hip and knee arthroplasty, respectively. The Norwegian mortality rates were 9.1 and 6.0 per 1,000 patient-years, respectively. The strongest predictors of death in the final models were age, sex, body mass index, and American Society of Anesthesiologists grade. Exposure variables related to the intervention, with the exception of knee arthroplasty type, did not add discrimination over patient factors alone. Discrimination was good in both cohorts, with c-indices above 0.76 for the hip and above 0.70 for the knee. Time-dependent Brier scores indicated appropriate estimation of the mortality rate (≤ 0.01, all models). Conclusion Simple demographic and clinical information may be used to calculate an individualized estimation for one-year mortality risk after hip or knee arthroplasty ( https://jointcalc.shef.ac.uk ). These models may be used to provide patients with an estimate of the risk of mortality after joint arthroplasty. Cite this article: Bone Joint Res 2020;9(11):808–820.
Background: Previous studies have suggested that the probability function of 1 minus the Kaplan-Meier survivorship overestimates revision rates of implants and that patient death should be included in estimates as a competing risk factor. The present study aims to demonstrate that this line of thinking is incorrect and is a misunderstanding of both the Kaplan-Meier method and competing risks. Methods: This study demonstrated the differences, misunderstandings, and interpretations of classical, competing-risk, and illness-death models with use of data from the Norwegian Arthroplasty Register for 15,734 cemented and 7,867 uncemented total hip arthroplasties (THAs) performed from 1987 to 2000, with fixation as the exposure variable. Results: The mean age was higher for patients who underwent cemented (72 years) versus uncemented THA (53 years); as such, a greater proportion of patients who underwent cemented THA had died during the time of the study (47% compared with 29%). The risk of revision at 20 years was 18% for cemented and 42% for uncemented THAs. The cumulative incidence function at 20 years was 11% for cemented and 36% for uncemented THAs. The prevalence of revision at 20 years was 6% for cemented and 31% for uncemented THAs. Conclusions: Adding death as a competing risk will always attenuate the probability of revision and does not correct for dependency between patient death and THA revision. Adjustment for age and sex almost eliminated differences in risk estimates between the different regression models. In the analysis of time until revision of joint replacements, classical survival analyses are appropriate and should be advocated. Level of Evidence: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.
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