Evidence map›Paper›PMID 41046307›Full record

ArticleTherapeutic innovation & regulatory science2026

Application of Bayesian Borrowing Methods in Clinical Trials for Children with Type II Diabetes Mellitus.

Roberto Crackel, Yuanyuan Ji, Yoonhee Kim, James Travis, Wenda Tu, Yun Wang, Sunghee Kim, Pablo Bonangelino

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Article in Therapeutic innovation & regulatory science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Roberto CrackelUnited States Food and Drug Administration, Silver Spring, MD, USA. Roberto.Crackel@fda.hhs.gov.ORCID http://orcid.org/0009-0000-2076-8912
Yuanyuan JiUniversity of Nebraska Medical Center, Omaha, USA.
Yoonhee KimUnited States Food and Drug Administration, Silver Spring, MD, USA.ORCID http://orcid.org/0009-0008-2630-1967
James TravisUnited States Food and Drug Administration, Silver Spring, MD, USA.ORCID http://orcid.org/0009-0000-6827-7768
Wenda TuUnited States Food and Drug Administration, Silver Spring, MD, USA.
Yun WangUnited States Food and Drug Administration, Silver Spring, MD, USA.ORCID http://orcid.org/0000-0003-1449-6214
Sunghee KimUnited States Food and Drug Administration, Silver Spring, MD, USA.
Pablo BonangelinoUnited States Food and Drug Administration, Silver Spring, MD, USA.ORCID http://orcid.org/0000-0001-9680-6081

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical trials for children with type II diabetes mellitus (T2DM) pose challenges often due to recruitment issues. The variability in the treatment effect for pediatrics with T2DM tends to be much larger than that for adults, therefore, a larger pediatric study is needed to independently detect a similar treatment effect. If leveraging adult information to a pediatric population can be appropriately justified, and scientific rational has been given for the relevancy of the adult information, then Bayesian borrowing methods can aid in reducing the number of patients needed for a pediatric study and therefore increase feasibility and efficiency. We introduce Bayesian borrowing methods to obtain scientifically sound and conclusive results with adequate study power in anti-diabetic products development for children with T2DM. To apply Bayesian borrowing methods, it is important to (1) identify the external data that can be leveraged, (2) pre-specify model parameters, (3) assess operating characteristics, and (4) pre-specify weights and the maximum amount of borrowing needed to achieve a study win. To protect against prior-data conflicts that may exist due to differences in T2DM between adults and pediatrics, we select a mixture prior to take an advantage that they adjust the degree of information borrowed based on the similarity between adults and pediatrics. We applied these methods to an anti-diabetic product. In conclusion, the outcomes of our step-by-step demonstration of the application of Bayesian borrowing methods provides a guide on how to pre-specify parameters and considerations that should be made when planning to implement said methods.

Indexed as

Clinical Trials as TopicDiabetes Mellitus, Type 2Hypoglycemic AgentsBayes TheoremChildHumansResearch DesignHypoglycemic AgentsBayesian borrowing methodsEffective sample size (ESS)Operating characteristicsType 2 diabetes mellitus in pediatrics

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.