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

Author

Listed:
  • Arroyo-Araujo, María

    (QUEST center for responsible research)

  • Carneiro, Clarissa França Dias
  • Piper, Sophie K.
  • Wilcke, Juliane C.

    (LMU Munich)

  • Ellenbach, Nicole
  • Boulesteix, Anne-Laure
  • Emprechtinger, Robbert
  • Haller, Bernhard
  • Ineichen, Benjamin V.
  • Riecken, Lars Björn

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

Suggested Citation

  • Arroyo-Araujo, María & Carneiro, Clarissa França Dias & Piper, Sophie K. & Wilcke, Juliane C. & Ellenbach, Nicole & Boulesteix, Anne-Laure & Emprechtinger, Robbert & Haller, Bernhard & Ineichen, Benja, 2024. "Data analysis planning and reporting for confirmatory multi-lab preclinical trials," MetaArXiv cnuh7, Center for Open Science.
    • Handle: RePEc:osf:metaar:cnuh7
    DOI: 10.31219/osf.io/cnuh7
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