An Application of Traditional and Emerging Methods for the Joint Analysis of Repeated Measurements with Time-to-Event Outcomes in Rheumatology

Details

• Alternative Title:
  Arthritis Care Res (Hoboken)
• Personal Author:
  Arbeeva, Liubov ; Nelson, Amanda E. ; Alvarez, Carolina ; Cleveland, Rebecca J. ; Allen, Kelli D. ; Golightly, Yvonne M. ; Jordan, Joanne M. ; Callahan, Leigh F. ; Schwartz, Todd A.
• Description:
  Objective:
  
  The goal of this paper is to describe approaches for the joint analysis of repeatedly measured data with time-to-event endpoints, 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 Project (JoCo OA) 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 endpoint of incident worsening of radiographic knee OA that was defined as an increased Kellgren-Lawrence (K-L) grade in at least one knee over time.
  
  Methods:
  
  First, we provide an overview of the methods for analyzing repeated measurements and time-to-event endpoints separately. Then, we describe traditional (Cox proportional hazards model, CoxPH) and emerging (joint model, JM) approaches allowing combined analysis of repeated measures with a time-to-event endpoint 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.
  
  Results:
  
  Applications of JM (but not CoxPH) showed that the risk of worsening radiographic OA is higher when BMI is higher or increasing, thus illustrating the advantages of JM for analyzing such dynamic measures in a longitudinal study.
  
  Conclusion:
  
  Joint models are preferable for simultaneous analyses of repeated measurement and time-to-event outcomes, particularly in a chronic disease context, where dependency between the time-to-event endpoint and the longitudinal trajectory of repeated measurements is inherent.
  
  
• Subjects:
  Article Body Mass Index Disease Progression Female Humans Incidence Joint Models Knee Joint Longitudinal Data Longitudinal Studies Male Obesity Osteoarthritis, Knee Predictive Value Of Tests Prognosis Repeated Measurements Rheumatology Risk Assessment Risk Factors Severity Of Illness Index Time-to-event Time Factors

  More +
• Source:
  Arthritis Care Res (Hoboken). 72(5):615-621
• Pubmed ID:
  30908869
• Pubmed Central ID:
  PMC6761043
• Document Type:
  Journal Article
• Funding:
  P60 AR049465/AR/NIAMS NIH HHS/United States ; U01 DP006266/DP/NCCDPHP CDC HHS/United States ; P60 AR030701/AR/NIAMS NIH HHS/United States ; U01DP006266/ACL/ACL HHS/United States ; P60 AR064166/AR/NIAMS NIH HHS/United States ; U01 DP003206/DP/NCCDPHP CDC HHS/United States
• Volume:
  72
• Issue:
  5
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:bd5cbd84f4cbe14cdda87731dc3d8d9e14393b54bc5045bee2079bce475df4b2
• Download URL:
  https://stacks.cdc.gov/view/cdc/87305/cdc_87305_DS1.pdf
• File Type:
  [PDF - 141.05 KB ]