ArticleBMC musculoskeletal disorders2021
Testing the proportional hazards assumption in cox regression and dealing with possible non-proportionality in total joint arthroplasty research: methodological perspectives and review.
Article in BMC musculoskeletal disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 2 of them syntheses that pooled it.
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Who cites it
90 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- Serological evidence linking viral infections to incident risk of hip and knee osteoarthritis.Bone & joint research · 2026Article
- Applications of Pharmacometrics in Antibody-Drug Conjugate Development.Pharmaceutics · 2026Review
- Antenatal Corticosteroid and Risk of Fractures in Children: A Nationwide Register Study.BJOG : an international journal of obstetrics and gynaecology · 2026Article
- A blood-based metabolomics study of cardiovascular diseases in Swedish twins reveals apolipoprotein B biology as important for myocardial infarction.GeroScience · 2026Article
- The Role of Dyads in Subjective Reporting and Prediction of Cognitive Worsening in Cognitively Unimpaired Individuals and Individuals with Subjective Cognitive Decline: Results of the CompAS Longitudinal Study.Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists · 2026Article
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- Cardiovascular Health and Outcomes in Carriers With Genetic Variants of Hypertrophic Cardiomyopathy.Mayo Clinic proceedings · 2026Article
30 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSurvival analysis and effect of covariates on survival time is a central research interest. Cox proportional hazards regression remains as a gold standard in the survival analysis. The Cox model relies on the assumption of proportional hazards (PH) across different covariates. PH assumptions should be assessed and handled if violated. Our aim was to investigate the reporting of the Cox regression model details and testing of the PH assumption in survival analysis in total joint arthroplasty (TJA) studies.
methodsWe conducted a review in the PubMed database on 28th August 2019. A total of 1154 studies were identified. The abstracts of these studies were screened for words "cox and "hazard*" and if either was found the abstract was read. The abstract had to fulfill the following criteria to be included in the full-text phase: topic was knee or hip TJA surgery; survival analysis was used, and hazard ratio reported. If all the presented criteria were met, the full-text version of the article was then read. The full-text was included if Cox method was used to analyze TJA survival. After accessing the full-texts 318 articles were included in final analysis.
resultsThe PH assumption was mentioned in 114 of the included studies (36%). KM analysis was used in 281 (88%) studies and the KM curves were presented graphically in 243 of these (87%). In 110 (45%) studies, the KM survival curves crossed in at least one of the presented figures. The most common way to test the PH assumption was to inspect the log-minus-log plots (n = 59). The time-axis division method was the most used corrected model (n = 30) in cox analysis. Of the 318 included studies only 63 (20%) met the following criteria: PH assumption mentioned, PH assumption tested, testing method of the PH assumption named, the result of the testing mentioned, and the Cox regression model corrected, if required.
conclusionsReporting and testing of the PH assumption and dealing with non-proportionality in hip and knee TJA studies was limited. More awareness and education regarding the assumptions behind the used statistical models among researchers, reviewers and editors are needed to improve the quality of TJA research. This could be achieved by better collaboration with methodologists and statisticians and introducing more specific reporting guidelines for TJA studies. Neglecting obvious non-proportionality undermines the overall research efforts since causes of non-proportionality, such as possible underlying pathomechanisms, are not considered and discussed.
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