ArticleActa orthopaedica2018
Different competing risks models for different questions may give similar results in arthroplasty registers in the presence of few events.
Article in Acta orthopaedica, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Patients With Femoral Neck Fractures Are at Risk for Conversion to Arthroplasty After Internal Fixation: A Machine-learning Algorithm.Clinical orthopaedics and related research · 2022Trial
- Association of the total cholesterol-high-density lipoprotein-glucose index with metabolic-associated steatotic liver disease: a 5-year retrospective cohort study.Frontiers in medicine · 2026Article
- Multiple Imputation of Missing Covariates When Using the Fine-Gray Model.Statistics in medicine · 2025Article
- Impact of Depression at HIV PrEP Initiation on Sustained PrEP Care Engagement Among US Gay and Bisexual Men.Journal of acquired immune deficiency syndromes (1999) · 2025Article
- Risk of recurrence in early-onset versus late-onset non-metastatic colorectal cancer, 2004-2019: a nationwide cohort study.The Lancet regional health. Europe · 2024Article
- Article
- Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.Clinical orthopaedics and related research · 2024Article
- CD4/CD8 Ratio Recovered as a Predictor of Decreased Liver Damage in Adults Infected With HIV: 16-Year Observational Cohort Study.JMIR public health and surveillance · 2024Observational
- Safety analysis of new medications in clinical trials: a simulation study to assess the differences between cause-specific and subdistribution frameworks in the presence of competing events.BMC medical research methodology · 2023Article
- A 15-year follow-up study of mortality in a pooled cohort of World Trade Center rescue and recovery workers.Environmental research · 2023Article
- Competing Risk Analysis: What Does It Mean and When Do We Need It in Orthopedics Research?The Journal of arthroplasty · 2021Article
- Population-based 10-year cumulative revision risks after hip and knee arthroplasty for osteoarthritis to inform patients in clinical practice: a competing risk analysis from the Dutch Arthroplasty Register.Acta orthopaedica · 2021Article
- Accounting for the Competing Risk of Death to Predict Kidney Failure in Adults With Stage 4 Chronic Kidney Disease.JAMA network open · 2021Article
- Contralateral breast cancer risk in patients with ductal carcinoma in situ and invasive breast cancer.NPJ breast cancer · 2020Article
- An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk.Contemporary clinical trials communications · 2020Article
- Competing mortality risks analysis of prediagnostic lifestyle and dietary factors in colorectal cancer survival: the Norwegian Women and Cancer Study.BMJ open gastroenterology · 2019Article
- Survival among Veterans Obtaining Dialysis in VA and Non-VA Settings.Journal of the American Society of Nephrology : JASN · 2019Article
- Article
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
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 data from the Dutch Arthroplasty Register (median follow-up 3.1 years, maximum 8 years), with sex, age, ASA score, diagnosis, and type of fixation as explanatory variables. The similarity of the resulting hazard ratios and confidence intervals was assessed visually and by computing the relative differences of the resulting subdistribution and cause-specific hazard ratios. Results - The outcomes of the cause-specific Cox and Fine-Gray regressions were numerically very close. The largest relative difference between the hazard ratios was 3.5%. Interpretation - The most likely explanation for the similarity is that there are relatively few events (revisions and deaths), due to the short follow-up compared with the expected failure-free survival of the hip and knee prostheses. Despite the similarity, we recommend always performing both cause-specific Cox and Fine-Gray regression. In this way, both etiology and prediction can be investigated.
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