Evidence map›Paper›PMID 39877553›Full record

ArticleEClinicalMedicine2025

CONSORT-DEFINE explanation and elaboration: recommendations for enhancing reporting quality and impact of early phase dose-finding clinical trials.

Jan Rekowski, Christina Guo, Olga Solovyeva, Munyaradzi Dimairo, Mahtab Rouhifard, Dhrusti Patel, Emily Alger, Deborah Ashby, Jordan Berlin, Oliver Boix and 28 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

38 authors.

Jan RekowskiClinical Trials and Statistics Unit at the Institute of Cancer Research, London, UK.
Christina GuoThe Institute of Cancer Research, London, UK.
Olga SolovyevaClinical Trials and Statistics Unit at the Institute of Cancer Research, London, UK.
Munyaradzi DimairoDivision of Population Health, Sheffield Centre for Health and Related Research, University of Sheffield, Sheffield, UK.
Mahtab RouhifardClinical Trials and Statistics Unit at the Institute of Cancer Research, London, UK.
Dhrusti PatelClinical Trials and Statistics Unit at the Institute of Cancer Research, London, UK.
Emily AlgerClinical Trials and Statistics Unit at the Institute of Cancer Research, London, UK.
Deborah AshbySchool of Public Health, Imperial College London, St Mary's Hospital, London, UK.
Jordan BerlinVanderbilt-Ingram Cancer Center, Nashville, TN, USA.
Oliver BoixBayer, Berlin, Germany.
Melanie CalvertCentre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
An-Wen ChanDepartment of Medicine, Women's College Research Institute, University of Toronto, Toronto, Canada.
Courtney H CoschiCanadian Cancer Trials Group, Kingston, ON, Canada.
Johann de BonoThe Institute of Cancer Research, London, UK.
Thomas R Jeffry EvansInstitute of Cancer Sciences, CR-UK Beatson Institute, University of Glasgow, Glasgow, UK.
Elizabeth Garrett-MayerCenter for Research and Analytics, American Society of Clinical Oncology, Alexandria, VA, USA.
Robert M GolubDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Kathryn S HaywardDepartments of Physiotherapy and Medicine, University of Melbourne, VIC, Australia.
Sally HopewellOxford Clinical Research Unit, NDORMS, University of Oxford, Oxford, UK.
John D IsaacsTranslational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.
S Percy IvyInvestigational Drug Branch, Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Institute of Health, Bethesda, MD, USA.
Thomas JakiMRC Biostatistics Unit, Cambridge University, Cambridge, UK.
Olga KholmanskikhFederal Agency for Medicines and Health Products, Brussels, Belgium.
Andrew KightleyPatient and Public Involvement and Engagement (PPIE) Lead, Lichfield, UK.
Shing LeeColumbia University Mailman School of Public Health, New York, NY, USA.
Rong LiuRegeneron, New York, NY, USA.
Israel MaiaHCor Research Institute, Sao Paulo, Brazil.
Adrian ManderCentre for Trials Research, Cardiff University, Cardiff, UK.
Lynley V MarshallThe Institute of Cancer Research, London, UK.
James MatchamStrategic Consulting, Cytel (Australia), Perth, WA, Australia.
Richard PeckDepartment of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK.
Khadija Rerhou RantellMedicines and Healthcare Products Regulatory Agency, London, UK.
Dawn P RichardsClinical Trials Ontario, MaRS Centre, Toronto, ON, Canada.
Lesley SeymourCanadian Cancer Trials Group, Kingston, ON, Canada.
Yoshiya TanakaFirst Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan.
Moreno UrsinoReCAP/F CRIN, INSERM, 5400, Nancy, France.
Christopher J WeirEdinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK.
Christina YapClinical Trials and Statistics Unit at the Institute of Cancer Research, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early phase dose-finding (EPDF) trials are key in the development of novel therapies, with their findings directly informing subsequent clinical development phases and providing valuable insights for reverse translation. Comprehensive and transparent reporting of these studies is critical for their accurate and critical interpretation, which may improve and expedite therapeutic development. However, quality of reporting of design characteristics and results from EPDF trials is often variable and incomplete. The international consensus-based CONSORT-DEFINE (Consolidated Standards for Reporting Trials Dose-finding Extension) statement, an extension of the CONSORT statement for randomised trials, was developed to improve the reporting of EPDF trials. The CONSORT-DEFINE statement introduced 21 new items and modified 19 existing CONSORT items.This CONSORT-DEFINE Explanation and Elaboration (E&E) document provides important information to enhance understanding and facilitate the implementation of the CONSORT-DEFINE checklist. For each new or modified checklist item, we provide a detailed description and its rationale with supporting evidence, and present examples from EPDF trial reports published in peer-reviewed scientific journals. When reporting the results of EPDF trials, authors are encouraged to consult the CONSORT-DEFINE E&E document, together with the CONSORT and CONSORT-DEFINE statement papers, and adhere to their recommendations. Widespread adoption of the CONSORT-DEFINE statement is likely to enhance the reporting quality of EPDF trials, thus facilitating the peer review of such studies and their appraisal by researchers, regulators, ethics committee members, and funders. Funding: This work is a further extension of the CONSORT-DEFINE study, which was funded by the UK Medical Research Council (MRC)-National Institute for Health and Care Research (NIHR) Methodology Research Programme (MR/T044934/1). The Clinical Trials and Statistics Unit at The Institute of Cancer Research (ICR-CTSU) receives programmatic infrastructure funding from Cancer Research UK (C1491/A25351; CTUQQR-Dec 22/100 004), which has contributed to accelerating the advancement and successful completion of this work.

Indexed as

CONSORTCONSORT-DEFINEDose escalation/de-escalationDose-findingEarly phase trialsPhase IReporting guidance

Identifiers

PMID39877553
PMCPMC11773258

What OpenQuestion holds

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LicenceCC BY-NC
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 OpenQuestion graph.