Data analysis planning and reporting for confirmatory multi-lab preclinical trials

María Arroyo-Araujo, Clarissa França Dias Carneiro, Sophie K. Piper, Juliane C. Wilcke, Nicole Ellenbach, Anne-Laure Boulesteix, Robbert Emprechtinger, Bernhard Haller, Benjamin V. Ineichen and Lars Björn Riecken
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María Arroyo-Araujo: QUEST center for responsible research
Juliane C. Wilcke: LMU Munich

No cnuh7, MetaArXiv from Center for Open Science

Abstract: Confirmatory multi-lab preclinical trials are a powerful experimental strategy to enable decisions to transition from preclinical to clinical settings. With their complexity, such study designs pose several challenges in analysing and reporting experiments. To address these, we convened an expert group of biostatisticians and biomedical scientists currently involved in such trials to summarise the most common scenarios. Furthermore, we incorporated statistical advice from existing clinical trials’ guidelines and adapted it into recommendations for future preclinical trials. We describe strategies on key topics such as calculating sample sizes, handling of differences between centres, and selecting relevant covariates. Additionally, we give guidance on statistical methods to account for lab effects and proper reporting of analyses. We embed this in a general discussion on remaining open questions to advance the analysis of preclinical confirmatory studies. The provided general, non-case-specific guidance serves as a conversation starter between scientists and statisticians to develop robust statistical analysis strategies for confirmatory multi-lab preclinical trials

Date: 2024-09-24
New Economics Papers: this item is included in nep-exp
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Persistent link: https://EconPapers.repec.org/RePEc:osf:metaar:cnuh7

DOI: 10.31219/osf.io/cnuh7

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