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Application of Heterogeneity of Treatment-Effects Methods: Exploratory Analyses of a Trial of Exercise-Based
Cynthia J Coffman1, Liubov Arbeeva2, Todd A Schwartz3
1Durham Veterans Administration Healthcare System and Duke University Medical Center, Durham, North Carolina.
Objective:
To evaluate heterogeneity of treatment effects in a trial of exercise-based interventions for knee osteoarthritis (OA).
Methods:
Participants (n = 350) were randomized to standard physical therapy (PT; n = 140), internet-based exercise training (IBET; n = 142), or wait list (WL; n = 68) control. We applied qualitative interaction trees (QUINT), a sequential partitioning method, and generalized unbiased interaction detection and estimation (GUIDE), a regression tree approach, to identify subgroups with greater improvements in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score over 4 months. Predictors included 24 demographic, clinical, and psychosocial characteristics. We conducted internal validation to estimate optimism (bias) in the range of mean outcome differences among arms.
Results:
Both QUINT and GUIDE indicated that for participants with lower body mass index (BMI), IBET was better than PT (improvements of WOMAC ranged from 6.3 to 9.1 points lower), and for those with higher BMI and a longer duration of knee OA, PT was better than IBET (WOMAC improvement was 6.3 points). In GUIDE analyses comparing PT or IBET to WL, participants not employed had improvements in WOMAC ranging from 1.8 to 6.8 points lower with PT or IBT versus WL. From internal validation, there were large corrections to the mean outcome differences among arms; however, after correction, some differences remained in the clinically meaningful range.
Conclusion:
Results suggest there may be subgroups who experience greater improvement in symptoms from PT or IBET, and this finding could guide referrals and future trials. However, uncertainty persists for specific treatment-effects size estimates and how they apply beyond this study sample.
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