ReviewArthritis care & research2020
Application of Traditional and Emerging Methods for the Joint Analysis of Repeated Measurements With Time-to-Event Outcomes in Rheumatology.
Review in Arthritis care & research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Weight loss and outcomes in subjects with progressive pulmonary fibrosis: data from the INBUILD trial.Respiratory research · 2023Trial
- Physical Activity and 4-Year Radiographic Medial Joint Space Loss in Knee Osteoarthritis: A Joint Model Analysis.The Journal of bone and joint surgery. American volume · 2026Article
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Authors and funding
9 authors.
Funding
Abstract
objectiveThe goal of this paper is to describe approaches for the joint analysis of repeatedly measured data with time-to-event end points, first separately and then in the framework of a single comprehensive model, emphasizing the efficiency of the latter approach. Data from the Johnston County Osteoarthritis (JoCo OA) Project will be used as an example to investigate the relationship between the change in repeatedly measured body mass index (BMI) and the time-to-event end point of incident worsening of radiographic knee OA that was defined as an increased Kellgren/Lawrence grade in at least 1 knee over time.
methodsFirst, we provide an overview of the methods for analyzing repeated measurements and time-to-event end points separately. Then, we describe traditional (Cox proportional hazards model [CoxPH]) and emerging (joint model [JM]) approaches, both of which allow combined analysis of repeated measures with a time-to-event end point in the framework of a single statistical model. Finally, we apply the models to JoCo OA data and interpret and compare the results from the different approaches.
resultsApplications of the JM (but not the CoxPH) showed that the risk of worsening radiographic OA is higher when BMI is higher or increasing, thus illustrating the advantages of the JM for analyzing such dynamic measures in a longitudinal study.
conclusionJoint models are preferable for simultaneous analyses of repeated measurement and time-to-event outcomes, particularly in the context of chronic disease, where dependency between the time-to-event end point and the longitudinal trajectory of repeated measurements is inherent.
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