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Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2
John M Dennis1, Katherine G Young1, Andrew P McGovern1
1University of Exeter Medical School, Institute of Biomedical and Clinical Science, Royal Devon and Exeter Hospital, Exeter, UK.
Background:
Current treatment guidelines do not provide recommendations to support the selection of treatment for most people with type 2 diabetes. We aimed to develop and validate an algorithm to allow selection of optimal treatment based on glycaemic response, weight change, and tolerability outcomes when choosing between SGLT2 inhibitor or DPP-4 inhibitor therapies.
Methods:
In this retrospective cohort study, we identified patients initiating SGLT2 and DPP-4 inhibitor therapies after Jan 1, 2013, from the UK Clinical Practice Research Datalink (CPRD). We excluded those who received SGLT2 or DPP-4 inhibitors as first-line treatment or insulin at the same time, had estimated glomerular filtration rate (eGFR) of less than 45 mL/min per 1·73 m2, or did not have a valid baseline glycated haemoglobin (HbA1c) measure (<53 or ≥120 mmol/mol). The primary efficacy outcome was the HbA1c value reached 6 months after drug initiation, adjusted for baseline HbA1c. Clinical features associated with differential HbA1c outcome on the two therapies were identified in CPRD (n=26 877), and replicated in reanalysis of 14 clinical trials (n=10 414). An algorithm to predict individual-level differential HbA1c outcome on the two therapies was developed in CPRD (derivation; n=14 069) and validated in head-to-head trials (n=2499) and CPRD (independent validation; n=9376). In CPRD, we further explored heterogeneity in 6-month weight change and treatment discontinuation.
Findings:
Among 10 253 patients initiating SGLT2 inhibitors and 16 624 patients initiating DPP-4 inhibitors in CPRD, baseline HbA1c, age, BMI, eGFR, and alanine aminotransferase were associated with differential HbA1c outcome with SGLT2 inhibitor and DPP-4 inhibitor therapies. The median age of participants was 62·0 years (IQR 55·0-70·0). 10 016 (37·3%) were women and 16 861 (62·7%) were men. An algorithm based on these five features identified a subgroup, representing around four in ten CPRD patients, with a 5 mmol/mol or greater observed benefit with SGLT2 inhibitors in all validation cohorts (CPRD 8·8 mmol/mol [95% CI 7·8-9·8]; CANTATA-D and CANTATA-D2 trials 5·8 mmol/mol [3·9-7·7]; BI1245.20 trial 6·6 mmol/mol [2·2-11·0]). In CPRD, predicted differential HbA1c response with SGLT2 inhibitor and DPP-4 inhibitor therapies was not associated with weight change. Overall treatment discontinuation within 6 months was similar in patients predicted to have an HbA1c benefit with SGLT2 inhibitors over DPP-4 inhibitors (median 15·2% [13·2-20·3] vs 14·4% [12·9-16·7]). A smaller subgroup predicted to have greater HbA1c reduction with DPP-4 inhibitors were twice as likely to discontinue SGLT2 inhibitors than DPP-4 inhibitors (median 26·8% [23·4-31·0] vs 14·8% [12·9-16·8]).
Interpretation:
A validated treatment selection algorithm for SGLT2 inhibitor and DPP-4 inhibitor therapies can support decisions on optimal treatment for people with type 2 diabetes.
Funding:
BHF-Turing Cardiovascular Data Science Award and the UK Medical Research Council.
Insights
A new algorithm helps select optimal type 2 diabetes treatments, choosing between SGLT2 inhibitors and DPP-4 inhibitors based on patient response and tolerability. This improves glycaemic control and treatment decisions.
Area of Science:
- Endocrinology
- Pharmacology
- Data Science in Medicine
Background:
- Current type 2 diabetes treatment guidelines lack specific recommendations for selecting between SGLT2 inhibitors and DPP-4 inhibitors.
- Optimal treatment selection requires consideration of glycaemic response, weight change, and tolerability.
Purpose of the Study:
- To develop and validate an algorithm for selecting optimal SGLT2 inhibitor or DPP-4 inhibitor therapy in type 2 diabetes.
- To identify clinical features associated with differential glycaemic response to these drug classes.
Main Methods:
- Retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD) and reanalysis of clinical trials.
- Development and validation of a predictive algorithm based on baseline HbA1c, age, BMI, eGFR, and alanine aminotransferase.
- Primary outcome: HbA1c at 6 months post-initiation; secondary outcomes: weight change and treatment discontinuation.
Main Results:
- An algorithm identified approximately 40% of patients benefiting more from SGLT2 inhibitors (e.g., 8.8 mmol/mol greater HbA1c reduction in CPRD).
- Baseline characteristics (HbA1c, age, BMI, eGFR, ALT) predicted differential HbA1c outcomes.
- Weight change was not associated with predicted differential response; discontinuation rates varied for subgroups favoring DPP-4 inhibitors.
Conclusions:
- A validated algorithm aids in selecting optimal SGLT2 inhibitor or DPP-4 inhibitor therapy for type 2 diabetes.
- The algorithm supports personalized treatment decisions based on predicted individual glycaemic response.
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