Evidence map›Paper›PMID 42504463›Full record

ReviewBiometrical journal. Biometrische Zeitschrift2026

Data Analysis Planning and Reporting for Confirmatory Multi-Lab Preclinical Trials: A Tutorial.

María Arroyo-Araujo, Clarissa F D Carneiro, Sophie K Piper, Juliane C Wilcke, Nicole Ellenbach, Anne-Laure Boulesteix, Robbert Emprechtinger, Benjamin V Ineichen, Lars Bjorn Riecken, Bernhard Haller and 4 more

Erratum issuedAbstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

María Arroyo-AraujoBerlin Institute of Health, Charité - Universitätsmedizin Berlin, QUEST Center for Responsible Research, Berlin, Germany.ORCID https://orcid.org/0000-0001-6612-0679
Clarissa F D CarneiroBerlin Institute of Health, Charité - Universitätsmedizin Berlin, QUEST Center for Responsible Research, Berlin, Germany.ORCID https://orcid.org/0000-0001-8127-0034
Sophie K PiperInstitute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-0147-8992
Juliane C WilckeInstitute for Medical Information Processing, Biometry, and Epidemiology, LMU Medizin, LMU Munich, Munich, Germany.ORCID https://orcid.org/0009-0005-7675-6669
Nicole EllenbachInstitute for Medical Information Processing, Biometry, and Epidemiology, LMU Medizin, LMU Munich, Munich, Germany.ORCID https://orcid.org/0000-0001-8298-0409
Anne-Laure BoulesteixInstitute for Medical Information Processing, Biometry, and Epidemiology, LMU Medizin, LMU Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-2729-0947
Robbert EmprechtingerBerlin Institute of Health, Charité - Universitätsmedizin Berlin, QUEST Center for Responsible Research, Berlin, Germany.ORCID https://orcid.org/0000-0003-3114-9812
Benjamin V IneichenDepartment of Clinical Research, University of Bern, Bern, Switzerland.ORCID https://orcid.org/0000-0003-1362-4819
Lars Bjorn RieckenLeibniz Institute on Aging, Fritz Lipmann Institute, Jena, Germany.ORCID https://orcid.org/0000-0002-1992-4591
Bernhard HallerInstitute of AI and Informatics in Medicine, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-9723-393X
Bernhard VoelklAnimal Welfare Division, University of Bern, Bern, Switzerland.ORCID https://orcid.org/0000-0001-5454-2508
Leonard HeldEpidemiology Biostatistics and Prevention Institute (EBPI) and Center for Reproducible Science (CRS), University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0002-8686-5325
Frank KonietschkeInstitute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-5674-2076
Ulf ToelchBerlin Institute of Health, Charité - Universitätsmedizin Berlin, QUEST Center for Responsible Research, Berlin, Germany.ORCID https://orcid.org/0000-0002-8731-3530

Funding

Bundesministerium für Bildung und Forschung 01KC1901ABundesministerium für Bildung und Forschung 01KC2003ABundesministerium für Bildung und Forschung 01KC2005Bundesministerium für Bildung und Forschung 01KC2012Bundesministerium für Bildung und Forschung 01KC2306German Research Foundation (DFG) BO3139/7German Research Foundation (DFG) BO3139/9
6 · The paper itself

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

BiometryAnimalsClinical Trials as TopicDrug Evaluation, PreclinicalHumansResearch Design

Identifiers

PMID42504463
PMCPMC13402973

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.