ArticleTherapeutic innovation & regulatory science2026
Application of Bayesian Borrowing Methods in Clinical Trials for Children with Type II Diabetes Mellitus.
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.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
41046307What OpenQuestion holds
Registered trials
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.