Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta‐regression analysis of 120 randomized controlled trials

Journal article

Aims: To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability. Methods: We used randomized clinical trials (RCTs) comparing glucose‐lowering drugs (including but not limited to sodium‐glucose cotransporter‐2 inhibitors, glucagon‐like peptide‐1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.e., treatment response heterogeneity) in verum (i.e., treatment) and placebo groups were included. Meta‐regression analyses were performed with respect to variability of body weight after treatment and potential predictors. Results: A total of 120 RCTs with a total of 43 663 participants were analysed. A slightly larger treatment response heterogeneity was shown in the verum groups, with a median log(SD) of 2.83 compared to 2.79 from placebo. After full adjustment in the meta‐regression model, the difference in body weight log(SD) was −0.026 (95% confidence interval −0.044; 0.008), with greater variability in the placebo groups. Scatterplots did not show any slope divergence (i.e., interaction) between clinical predictors and the respective treatment (verum or placebo). Conclusions: We found no major treatment response heterogeneity in RCTs of glucose‐lowering drugs for body weight reduction in type 2 diabetes. The precision medicine approach may thus be of limited value in this setting.

Authors: Vargas, KG; Rütten, T; Siemes, B; Brockmeyer, M; Parco, C

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Diabetes, Obesity and Metabolism
• Publication date: 2024-02-29
• Acceptance date: 2024-02-05
• DOI: 10.1111/dom.15519
• EISSN: 1463-1326
• ISSN: 1462-8902 and 1463-1326
• Language: English
• Keywords: SGLT2 inhibitor; meta‐regression analysis; GLP‐1 receptor agonist; obesity; type 2 diabetes mellitus; body weight reduction; precision medicine