Validation of a treatment selection algorithm for optimal choice of SGLT2 and DPP4 inhibitor therapies in people with type 2 diabetes across major UK ethnicity groups

Abstract

Background Targeting type 2 diabetes treatments based on the routine clinical features of individual patients represents a practical precision medicine approach with potential worldwide applicability. 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.

Methods We 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 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.

Results SGLT2i (n=57,749) and DPP4i (n=87,807) initiations were identified amongst people of White (n=114,287; 78.5%), Black (n=6,663; 4.6%), South Asian (n=20,969; 14.4%) and Mixed/Other (n=3,637; 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, calibration of predicted differential glycaemic treatment effects were well-calibrated.

Conclusion A treatment selection model for SGLT2-inhibitor and DPP4-inhibitor therapies is accurate for all major UK ethnicity groups. Simple recalibration is beneficial to optimise performance and this is recommended prior to deployment of the model in new populations and settings.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

The authors acknowledge support from the Medical Research Council (UK) (MR/N00633X/1), the National Institute for Health and Care Research (NIHR) Exeter Biomedical Research Centre (BRC), and EFSD/Novo Nordisk. ATH and BMS are supported by the NIHR Exeter Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

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This article is based in part on data from the Clinical Practice Research Datalink obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. CPRD data is provided by patients and collected by the NHS as part of their care and support. Approval for CPRD data access and the study protocol was granted by the CPRD Independent Scientific Advisory Committee (eRAP protocol number: 24_004747).

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