Pieter Colin 1,2, Efthymios Manolis 1, Jeroen Koomen 2,3
1 European Medicines Agency (Amsterdam, The Netherlands), 2 Department of Anesthesiology, University of Groningen, University Medical Center Groningen (Groningen, The Netherlands), 3 Department of Pharmacology, Toxicology and Kinetics, Dutch Medicines Evaluation Board (Utrecht, The Netherlands)
Introduction: The efficacy of a new medicinal drug product indicated for the treatment or prevention of Type 2 Diabetes Mellitus (T2DM) in pediatric patients aged 10 years and older is generally established with one randomized placebo-controlled clinical trial, in which the change from baseline in glycated hemoglobin (HbA1c), as surrogate marker for glycemic control, is compared between the new medicinal product and placebo (ΔHbA1c) [1]. This evidence generation strategy remains however challenging, with most randomized trials failing to demonstrate statistically significant reductions in HbA1c, partly due to substantial between‑subject variability [2-5]. For pediatric drug development, innovative trial designs and model-based methods have been suggested to expedite the development of novel treatments [2,6]. This study presents a model-based longitudinal meta-analysis of HbA1c concentrations in pediatric patients aged 10 years and older living with T2DM from data submitted to EMA to support marketing authorization applications in the EU.
Objectives:
• To quantify between-subject variability in HbA1c concentrations and the contribution of intrinsic and extrinsic factors to this variability.
• To evaluate the power to detect a significant treatment effect using conventional efficacy analysis and trial design.
• To explore strategies to improve pediatric evidence generation for future trials.
Methods: Data was extracted for all medicinal drug products, indicated for the treatment or prevention of T2DM, with a compliant pediatric investigation plan. A linear mixed-effects model, with structural model components representing baseline, disease progression, placebo-response and drug-effect, was fitted to the longitudinal HbA1c data. Covariates evaluated for inclusion in the model were age, weight, body mass index, time since diagnosis, sex, and background therapy. Model parameters were estimated using the importance sampling algorithm with interaction in NONMEM (Version 7.5; GloboMax LLC, Hanover, MD, USA). Clinical trial simulations were conducted with virtual trials of different sample size (up to 1400 patients) and assuming different placebo-corrected treatment effects (ΔHbA1c ranging from -0.3 to -1.0%). The probability to detect a significant treatment effect as a function of trial size and placebo-corrected treatment effect was explored using different strategies.
Results: The analysis incorporated 3295 HbA1c concentrations from 809 participants. Baseline HbA1c was 7.46% (95% confidence intervals [CI]: 7.29% to 7.64%) and increased 1.13 (95% CI: 1.07 to 1.22) fold per year. The placebo response decreased HbA1c concentrations with a half-life of 6.85 weeks (95 % CI: 5.17 to 9.06) and a magnitude of 7% (95% CI: 4% to 12%) of the baseline, i.e. a 0.52 %-point decrease for a typical baseline HbA1c concentration. Insulin use and longer duration of diabetes were associated with higher baseline HbA1c and/or faster disease progression, while the placebo effect was substantial and highly variable across participants. All estimated placebo-corrected treatment effects were positive and typically ranged from -0.14% to -1.05%-points in HbA1c. Clinical trial simulations demonstrated that trials with fewer than 200 participants are unlikely to achieve 80% power to detect a significant placebo‑corrected treatment effect smaller than –0.70 %-points over 26 weeks. Enrichment strategies targeting patients with lower variability, as well as model‑based estimators, including Bayesian approaches leveraging historical information, substantially reduced the required sample size.
Conclusions: These findings indicate that current pediatric T2DM trials are typically underpowered due to underestimation of variability in HbA1c and highlight opportunities for more efficient trial designs. By quantifying disease‑ and treatment‑related drivers of HbA1c trajectories and demonstrating the potential of model‑informed strategies to improve power, this work provides a framework to enhance pediatric T2DM drug development and support regulatory decision‑making.
References:
1. Van der Schueren B, Vrijlandt P, Thomson A, Janssen H, Dunder K. New guideline of the European Medicines Agency (EMA) on the clinical investigation of medicinal products in the treatment and prevention of diabetes mellitus. Diabetologia. Jul 2024;67(7):1159–1162. doi:10.1007/s00125-024-06162-z
2. Currie BM, Howell TA, Matza LS, Cox DA, Johnston JA. A Review of Interventional Trials in Youth-Onset Type 2 Diabetes: Challenges and Opportunities. Diabetes Ther. Nov 2021;12(11):2827–2856. doi:10.1007/s13300-021-01136-5
3. Meeting highlights from the Committee for Medicinal Products for Human Use (CHMP). European Medicines Agency. Accessed 05/09/2025, https://www.ema.europa.eu/en/news?f%5B0%5D=ema_news_responsible_body%3A100002
4. Shah AS, Barrientos-Perez M, Chang N, et al. ISPAD Clinical Practice Consensus Guidelines 2024: Type 2 Diabetes in Children and Adolescents. Horm Res Paediatr. 2024;97(6):555–583. doi:10.1159/000543033
5. Barrett T, Jalaludin MY, Turan S, Hafez M, Shehadeh N, Novo Nordisk Pediatric Type 2 Diabetes Global Expert P. Rapid progression of type 2 diabetes and related complications in children and young people-A literature review. Pediatr Diabetes. Mar 2020;21(2):158–172. doi:10.1111/pedi.12953
6. Barrett JS, Bucci-Rechtweg C, Amy Cheung SY, et al. Pediatric Extrapolation in Type 2 Diabetes: Future Implications of a Workshop. Clin Pharmacol Ther. Jul 2020;108(1):29–39. doi:10.1002/cpt.1805
Reference: PAGE 34 (2026) Abstr 12299 [www.page-meeting.org/?abstract=12299]
Poster: Drug/Disease Modelling - Other Topics