ReviewBiometrical journal. Biometrische Zeitschrift2026
Data Analysis Planning and Reporting for Confirmatory Multi-Lab Preclinical Trials: A Tutorial.
Review in Biometrical journal. Biometrische Zeitschrift, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Strengthening translational preclinical research through confirmatory multi-laboratory studies.Frontiers in medicine · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
14 authors.
Funding
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 statistical planning, analysis, and reporting of experiments. To address these, we convened an expert group of biostatisticians and biomedical scientists currently involved in such trials to summarize in a tutorial the most common challenges and offer general guidance. Furthermore, we incorporated statistical advice from existing clinical trials' guidelines and adapted it into recommendations for preclinical trials. We describe strategies on key topics such as calculating sample sizes, handling differences between centers, 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 biomedical scientists and statisticians to develop robust statistical analysis strategies for confirmatory multi-lab preclinical trials.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.