Evidence map›Paper›PMID 39572512›Full record

ArticleTherapeutic innovation & regulatory science2025

Comparison of Borrowing Methods for Incorporating Historical Data in Single-Arm Phase II Clinical Trials.

Sara Urru, Michela Verbeni, Danila Azzolina, Ileana Baldi, Paola Berchialla

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Therapeutic innovation & regulatory science, 2025. 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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2 · The registry

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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

5 authors.

Sara UrruUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Michela VerbeniUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Danila AzzolinaDepartment of Environmental Sciences and Prevention, University of Ferrara, Ferrara, Italy.
Ileana BaldiUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Paola BerchiallaCentre for Biostatistics, Epidemiology and Public Health, Department of Clinical and Biological Sciences, University of Turin, Regione Gonzole 10, Orbassano, 10043, Italy. paola.berchialla@unito.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOver the last few years, many efforts have been made to leverage historical information in clinical trials. Incorporating historical data into current trials allows for a more efficient design, smaller studies, or shorter duration and may potentially increase the relative amount of information on efficacy and safety. Despite these advantages, it is crucial to select external data sources appropriately to avoid introducing potential bias into the new study. This is where borrowing methods become useful. We illustrate and compare the latest methods of borrowing historical data in a single-arm phase II clinical trial setting, examining their impact on statistical power and type I error.

methodsWe implemented static and dynamic versions of the power prior method, incorporating overlapping coefficient and loss functions and meta-analytic predictive priors. These methods were compared with standard and pooling approaches, in which none or all historical data are used.

resultsDynamic borrowing methods achieve lower type I error inflation than pooling. The power prior approach, integrated with overlapping coefficient, allowed for measuring the similarity of the subjects considering their baseline characteristics, thus the likelihood of the data contains information about both confounders and outcome. Using a discounting function to estimate the power parameter guarantees the similarity of historical information and current trial data.

conclusionWe provided a comprehensive overview of borrowing methods, encompassing frequentist and Bayesian approaches as well as static and dynamic technique, to guide researchers in selecting the most appropriate strategy.

Indexed as

Clinical Trials, Phase II as TopicResearch DesignBayes TheoremHumansBayesianHistorical dataInformation borrowingMap priorPower priorsSimulation

Identifiers

PMID39572512

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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.