Heterogeneity of Treatment Effects Among Patients With Type 2 Diabetes and Elevated Body Mass Index in a Study Comparing Group Medical Visits Focused on Weight Management and Medication Intensification. Issue 11 (13th November 2021)

• Record Type: Journal Article
• Authors: Kobe, Elizabeth A.; Crowley, Matthew J.; Jeffreys, Amy S.; Yancy, William S.; Zervakis, Jennifer; Edelman, David; Voils, Corrine I.; Maciejewski, Matthew L.; Coffman, Cynthia J.
• Is Part Of: Medical care. Volume 59:Issue 11(2021)
• Page Start: 1031
• Page End: 1038
• Publication Date: 2021-11-13
• Subjects: QUINT -- heterogeneity of treatment effect -- diabetes -- weight management -- health services research; Economics, Medical -- Periodicals; Insurance, Health -- Periodicals; Santé, Services de -- Administration -- Périodiques; Soins médicaux -- Périodiques; Medical economics -- Periodicals; Health insurance -- Periodicals; Medical economics -- United States -- Periodicals; Health insurance -- United States -- Periodicals; Comprehensive Health Care -- Periodicals; Personal Health Services -- Periodicals; Gezondheidszorg; Économie de la santé -- Périodiques; Santé, Services de -- Périodiques; Health insurance; Medical economics; United States; Periodicals; 362.10973
• DOI: 10.1097/MLR.0000000000001642
• Languages: English
• ISSNs: 0025-7079

Abstract

Abstract : Supplemental Digital Content is available in the text. Abstract : Background: Illuminating heterogeneity of treatment effect (HTE) within trials is important for identifying target populations for implementation. Objective: The aim of this study was to examine HTE in a trial of group medical visits (GMVs) for patients with type 2 diabetes and elevated body mass index. Research Design and Measures: Participants (n=263) were randomized to GMV-based medication management plus low carbohydrate diet-focused weight management (WM/GMV; n=127) or GMV-based medication management alone (GMV; n=136) for diabetes control. We used QUalitative INteraction Trees, a tree-based clustering method, to identify subgroups with greater improvement in hemoglobin A1c (HbA1c) and weight from either WM/GMV or GMV. Subgroup predictors included 32 baseline demographic, clinical, and psychosocial factors. Internal validation was conducted to estimate bias in the range of mean outcome differences between arms. Results: QUalitative INteraction Trees analyses indicated that for patients who had not previously attempted weight loss, WM/GMV resulted in better glycemic control than GMV (mean difference in HbA1c improvement=1.48%). For patients who had previously attempted weight loss and had lower cholesterol and blood urea nitrogen, GMV was better than WM/GMV (mean difference in HbA1c improvement=1.51%). No treatment-subgroup effects were identified for weight. Internal validation resulted in moderate corrections in mean HbA1c differences between arms; however, differences remained in the clinically significant range. Conclusion: This work represents a novel step toward targeting care approaches for patients to maximize benefit based on individual patient characteristics.