ArticleBiometrical journal. Biometrische Zeitschrift2020
Power gains by using external information in clinical trials are typically not possible when requiring strict type I error control.
Article in Biometrical journal. Biometrische Zeitschrift, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Pharmacometrics-Enhanced Bayesian Borrowing for Pediatric Extrapolation - A Case Study of the DINAMO Trial.Therapeutic innovation & regulatory science · 2025Trial
- Augmenting randomized clinical trial data with historical control data: Precision medicine applications.Journal of the National Cancer Institute · 2023Trial
- On the relevance of prognostic information for clinical trials: A theoretical quantification.Biometrical journal. Biometrische Zeitschrift · 2023Trial
- Challenges, opportunities, and innovative statistical designs for precision oncology trials.Annals of translational medicine · 2022Trial
- The use of local and nonlocal priors in Bayesian test-based monitoring for single-arm phase II clinical trials.Pharmaceutical statistics · 2021Trial
- Bayesian sample size determination using robust commensurate priors with interpretable discrepancy weights.Statistical methods in medical research · 2026Article
- A Bayesian Adaptive Marker-Stratified Design for Phase II Clinical Trials Using Calibrated Spike-and-Slab priors.Statistics in biopharmaceutical research · 2026Article
- Incorporating historic information to further improve power when conducting Bayesian information borrowing in basket trials.Biostatistics (Oxford, England) · 2025Article
- A digital twin methodology using real patient data for sample size reduction in Alzheimer's disease randomized controlled clinical trials.medRxiv : the preprint server for health sciences · 2025Article
- On the Two-Step Hybrid Design for Augmenting Randomized Trials Using Real-World Data.Statistics in biopharmaceutical research · 2025Article
- Augmenting Treatment Arms With External Data Through Propensity-Score Weighted Power Priors: An Application in Expanded Access.Statistics in medicine · 2025Article
- Statistical Modeling to Adjust for Time Trends in Adaptive Platform Trials Utilizing Non-Concurrent Controls.Biometrical journal. Biometrische Zeitschrift · 2025Article
- How to add baskets to an ongoing basket trial with information borrowing.Statistical methods in medical research · 2025Article
- Utility-based optimization of Fujikawa's basket trial design - Pre-specified protocol of a comparison study.PloS one · 2025Article
- Evaluation of the Fill-it-up-design to use historical control data in randomized clinical trials with two arm parallel group design.BMC medical research methodology · 2024Article
- Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review.BMC medical research methodology · 2024Review
- Streamlining Randomized Clinical Trials for Device Therapies in Heart Failure: Bayesian Borrowing of External Data.Journal of the American Heart Association · 2024Article
- Bayesian methods: a potential path forward for sepsis trials.Critical care (London, England) · 2023Article
- Improved efficiency for cross-arm comparisons via platform designs.Biostatistics (Oxford, England) · 2023Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In the era of precision medicine, novel designs are developed to deal with flexible clinical trials that incorporate many treatment strategies for multiple diseases in one trial setting. This situation often leads to small sample sizes in disease-treatment combinations and has fostered the discussion about the benefits of borrowing of external or historical information for decision-making in these trials. Several methods have been proposed that dynamically discount the amount of information borrowed from historical data based on the conformity between historical and current data. Specifically, Bayesian methods have been recommended and numerous investigations have been performed to characterize the properties of the various borrowing mechanisms with respect to the gain to be expected in the trials. However, there is common understanding that the risk of type I error inflation exists when information is borrowed and many simulation studies are carried out to quantify this effect. To add transparency to the debate, we show that if prior information is conditioned upon and a uniformly most powerful test exists, strict control of type I error implies that no power gain is possible under any mechanism of incorporation of prior information, including dynamic borrowing. The basis of the argument is to consider the test decision function as a function of the current data even when external information is included. We exemplify this finding in the case of a pediatric arm appended to an adult trial and dichotomous outcome for various methods of dynamic borrowing from adult information to the pediatric arm. In conclusion, if use of relevant external data is desired, the requirement of strict type I error control has to be replaced by more appropriate metrics.
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