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Updated: Mar 23, 2026

In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
Towards high-quality and timely interim analyses in adaptive trials: a scoping review of best practice and evidence
Katie H Thomson1,2, Opeyemi Agbeleye3,4, Chizoba Oparah3,4
1Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, NE2 4BN, UK. katie.thomson@newcastle.ac.uk.
Background:
Adaptive designs (ADs) are increasingly used, whereby outcome data accumulated during the trial may inform a trial's course in accordance with pre-specified rules at interim analyses. The benefits however will only be realised if the approaches to conducting interim analyses are optimised. This study aims to identify existing literature highlighting best practice (and existing evidence gaps) with regard to conducting high-quality, timely interim analyses.
Methods:
Medline and Embase databases were searched for studies published between 2005 and July 2025 to identify best practice models and lessons learned for interim analyses in the delivery of adaptive trials. Specifically, we considered papers that discussed adaptive trial methodological approaches (Phases II-IV) in any clinical population and condition. A narrative synthesis focused on the following outcomes was conducted: design considerations, project/trial management, data management, statistical processes, trial committee processes, the implementation of interim decisions and patient and public involvement and engagement (PPIE).
Results:
We screened 6720 articles from databases and citation chaining and assessed 329 articles at full text. One hundred and one articles representing 92 unique studies were deemed eligible for inclusion. Key issues included the following: (a) Detailed planning of interim analyses set out in the protocol, and all patient information sheets for possible changes prepared in advance; (b) Effective communication and collaborative decision-making processes across stakeholders, effective staff training, and prompt site query resolutions; (c) Use of electronic data capture with automated data flow processes with integrated query processes to improve data quality; and (d) Use of secure databases with data transfer procedures to maintain data integrity.
Conclusion:
The currently available data suggest that although there is a considerable volume of evidence with regards to the conduct of adaptive trials and good trial management, the existing literature base offers limited specific guidance for interim analyses. There are significant gaps in the literature regarding best practice guidance related to PPIE and statistical considerations in adaptive trials. While there are examples of innovative methods speeding up the collation and analysis of data used for interim analyses, we advocate more robust research exploring the operational opportunities and challenges with regards to undertaking adaptive trials.
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