Validation of an algorithm for selection of SGLT2 and DPP4 inhibitor therapies in people with type 2 diabetes across major UK ethnicity groups: a retrospective cohort study

Journal article

BackgroundRoutine clinical features of individual patients can potentially be used to guide selection of type 2 diabetes treatments. We aimed to evaluate a recently proposed treatment selection model predicting differences in glycaemic responses to SGLT2-inhibitors and DPP4-inhibitors across major UK ethnicity groups.MethodsWe externally validated the SGLT2i-DPP4i model in UK primary care cohort (CPRD Aurum, 2013-2020) independent of the original model development cohort. Non-insulin treated individuals with type 2 diabetes were identified and categorised by major UK self-reported ethnicity groups: White, Black, South Asian and Mixed/Other. For each ethnicity group, we applied a closed testing procedure to assess whether model recalibration was required. After model updates, we assessed the calibration accuracy of predicted differences in glycaemic response (6-month change in HbA1c) between SGLT2i and DPP4i for each ethnicity group.FindingsSGLT2i (n = 57,749) and DPP4i (n = 87,807) initiations were identified amongst people of White (n = 114,287; 78.5%), Black (n = 6663; 4.6%), South Asian (n = 20,969; 14.4%) and Mixed/Other (n = 3637; 2.5%) ethnicities. Minor model adjustment was required to adjust for greater observed than predicted glycaemic responses to DPP4i (White-1.6 mmol/mol; Black-3.0 mmol/mol; South Asian-2.6 mmol/mol; Mixed/Other-2.6 mmol/mol). SGLT2i predictions did not require adjustment for non-White ethnicity groups. After model updates, average predicted HbA1c reduction was 3.7 mmol/mol (95% CI 3.5-3.9) greater with SGLT2i than DPP4i for those of White ethnicity; this was greater than for those of South Asian (2.1 mmol/mol (95% CI 1.6-2.6)), Black (0.6 mmol/mol (95% CI 0.5-1.7)) and Mixed/Other (2.6 mmol/mol (95% CI 1.4-3.8)) ethnicity groups. For all ethnicity groups, predicted differential glycaemic treatment effects were well calibrated.InterpretationOur model for selection of SGLT2-inhibitor and DPP4-inhibitor therapies was accurate for all major self-reported ethnicity groups in a UK primary care cohort. Simple recalibration is beneficial to optimise performance and this is recommended prior to deployment of the model in new populations and settings.FundingUK Medical Research Council, National Institute for Health and Care Research Exeter Biomedical Research Centre, and EFSD/Novo Nordisk.

Authors: Güdemann, LM; Young, KG; Cardoso, P; Mateen, BA; Holman, RR

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Elsevier
• Journal: The Lancet Regional Health Europe
• Volume: 61
• Pages: 101547
• Publication date: 2025-11-27
• Acceptance date: 2025-11-12
• DOI: 10.1016/j.lanepe.2025.101547
• EISSN: 2666-7762
• ISSN: 2666-7762
• Pmid: 41399804
• Language: English
• Keywords: Precision Medicine; Heterogeneous Treatment Effects; Ethnicity; Personalised Medicine; Sglt2-inhibitors; Dpp4-inhibitors; Type 2 diabetes