Heterogeneity of Treatment Effects Across Nine Glucose-Lowering Drug Classes in Type 2 Diabetes: Extension of the...

Understanding heterogeneous responses to glucose-lowering therapies is crucial for advancing personalized treatment and optimizing outcomes in type 2 diabetes mellitus (T2DM). While average treatment effects are established for many drug classes, responses may vary by clinical and demographic factors. Here, we evaluated whether major glucose-lowering drug classes exhibit heterogeneous treatment effects (HTE) across key patient characteristics.

This large-scale observational cohort study was replicated in six data-sources across the Observational Health Data Sciences and Informatics network. New-user, active-comparator cohorts were constructed for patients with T2DM initiating one of the nine antihyperglycemic drug classes. Large-scale propensity score adjustment, empirical calibration using negative controls, and random-effects meta-analysis were used to estimate calibrated hazard ratios (HRs). HTE was assessed by comparing differences in log HRs across clinical and demographic subgroups.

Nominal signals of HTE were observed in the hyperlipidemia, hypertension, obesity, and sex subgroups: Biguanides (vs. DPP-4 inhibitors) were associated with lower risk of acute myocardial infarction in hyperlipidemia and heart failure hospitalization in obesity. SGLT-2 inhibitors (vs. GLP-1 receptor agonists) were associated with reduced stroke risk only in non-obese patients. Sex-specific patterns included higher risk of diarrhoea with GLP-1 receptor agonists and lower risk of stroke with SGLT-2 inhibitors (both vs. DPP-4 inhibitors) in women. None of the signals demonstrated statistical significance after multiple testing correction. Several subgroups (e.g., diabetic ketoacidosis and retinopathy) did not meet diagnostic criteria for clinical reliability and were not evaluated.

This hypothesis-generating study identified limited signals of HTE. These findings are exploratory and require cautious interpretation and validation.