medRxiv : the preprint server for health sciences · 2026
Heterogeneity of Treatment Effects Across Nine Glucose-Lowering Drug Classes in Type 2 Diabetes: Extension of the LEGEND-T2DM Network Study.
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Chen Hsin Yi, Falconer Thomas, Ostropolets Anna, Anand Tara V, Jiang Xinzhuo, Dávila-García David, Zhang Linying, Fan Ruochong, Morgan-Cooper Hannah, Suchard Marc A, Hripcsak George
Аннотация
AIMS/HYPOTHESIS: Understanding heterogeneous patient responses to various glucose-lowering therapies is crucial for advancing personalized treatment approaches and optimizing outcomes for type 2 diabetes mellitus. While average treatment effects are known for many drug classes, patient responses may differ by underlying clinical and demographic factors. We hypothesize that major glucose-lowering drug classes exhibit heterogeneous treatment effects (HTE) across patient subgroups defined by key clinical and demographic characteristics.
METHODS: This is a large-scale observational cohort study replicated in six data-sources across the Observational Health Data Sciences and Informatics network. New-user, active-comparator cohorts were constructed for patients with type 2 diabetes mellitus initiating one of the nine antihyperglycemic drug classes. Large-scale propensity score adjustment for measured confounding, empirical calibration using negative control outcomes, and random-effects meta-analysis were employed to estimate calibrated hazard ratios (HRs). HTE was assessed by comparing differences in log HRs across 10 demographic and clinical subgroups.
RESULTS: Evidence of HTE was observed across hyperlipidemia, hypertension, obesity, and sex subgroups. Biguanides (vs. DPP-4i) were protective against acute myocardial infarction in patients with hyperlipidemia, and against heart failure hospitalization in patients with obesity. SGLT-2 inhibitors (vs. GLP-1 receptor agonists) reduced stroke risk only in non-obese patients. Sex-specific patterns also emerged: women taking GLP-1 receptor agonists had a higher risk of diarrhea, and women taking SGLT-2 inhibitors had a lower risk of stroke compared with DPP-4 inhibitors; these associations were not seen for male patients.
CONCLUSIONS: This hypothesis-generating study identified several potential signals (blood pressure status, lipid status, obesity status, and sex) where there exists treatment effect heterogeneity for several classes of type 2 diabetes mellitus drugs. These preliminary findings highlight the potential for personalized type 2 diabetes mellitus treatment recommendations based on patient characteristics.
METHODS: This is a large-scale observational cohort study replicated in six data-sources across the Observational Health Data Sciences and Informatics network. New-user, active-comparator cohorts were constructed for patients with type 2 diabetes mellitus initiating one of the nine antihyperglycemic drug classes. Large-scale propensity score adjustment for measured confounding, empirical calibration using negative control outcomes, and random-effects meta-analysis were employed to estimate calibrated hazard ratios (HRs). HTE was assessed by comparing differences in log HRs across 10 demographic and clinical subgroups.
RESULTS: Evidence of HTE was observed across hyperlipidemia, hypertension, obesity, and sex subgroups. Biguanides (vs. DPP-4i) were protective against acute myocardial infarction in patients with hyperlipidemia, and against heart failure hospitalization in patients with obesity. SGLT-2 inhibitors (vs. GLP-1 receptor agonists) reduced stroke risk only in non-obese patients. Sex-specific patterns also emerged: women taking GLP-1 receptor agonists had a higher risk of diarrhea, and women taking SGLT-2 inhibitors had a lower risk of stroke compared with DPP-4 inhibitors; these associations were not seen for male patients.
CONCLUSIONS: This hypothesis-generating study identified several potential signals (blood pressure status, lipid status, obesity status, and sex) where there exists treatment effect heterogeneity for several classes of type 2 diabetes mellitus drugs. These preliminary findings highlight the potential for personalized type 2 diabetes mellitus treatment recommendations based on patient characteristics.