Optimising Prescribing in Type 2 Diabetes: Updating a Five-Drug Class Treatment Selection Model to Include NewerGLP-1 Receptor Agonists

by Prateek Chopra | June 29, 2026 | Diabetes Conferences | ADA 2026

Precision Medicine in T2D

  • Personalized treatment selection may improve outcomes by identifying therapies most likely to benefit individual patients.
  • This study expanded a validated treatment response prediction model to include both oral and subcutaneous semaglutide.

Methods

  • Data were obtained from the UK Clinical Practice Research Datalink (CPRD Aurum).
  • Non-insulin-treated individuals initiating semaglutide therapy through June 2024 were included.
  • The primary outcome was change in HbA1c at 12 months.
  • External validation was performed using the Scottish Diabetes Research Network (SDRN).

Study Population

  • Oral semaglutide initiations: 3,056.
  • Subcutaneous semaglutide initiations: 6,969.
  • Mean baseline HbA1c: 74 ± 13 mmol/mol.
  • Mean age: 59 ± 11 years.
  • Mean BMI: 36 ± 7 kg/m².
  • Mean eGFR: 93 ± 18 ml/min/1.73m².
  • Male participants: 55%.

Model Performance

  • HbA1c responses to oral semaglutide closely matched predictions derived from other GLP-1 receptor agonists.
  • No model modification was required for oral semaglutide.
  • Responses to subcutaneous semaglutide followed similar patterns but showed greater HbA1c reductions than predicted.

Key Findings

  • Subcutaneous semaglutide achieved an additional HbA1c reduction of 7.0 mmol/mol (95% CI: 6.2–7.8) compared with other GLP-1 receptor agonists.
  • An intercept adjustment improved model calibration for subcutaneous semaglutide.
  • The revised model demonstrated excellent calibration during external validation in 2,951 semaglutide users from SDRN.

Clinical Implications

  • The updated model can accurately estimate individual glycemic responses across multiple glucose-lowering therapies, including semaglutide.
  • Such tools may support more personalized and evidence-based treatment selection in routine clinical practice.

The updated five-drug class prediction model accurately predicts HbA1c responses to both oral and subcutaneous semaglutide. Successful external validation supports its use as a precision medicine tool for individualized treatment selection in type 2 diabetes.

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