CONSORT-DEFINE explanation and elaboration: recommendations for enhancing reporting quality and impact of early phase dose-finding clinical trials
Bibliographic record
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.625 | 0.843 |
| Meta-epidemiology (narrow) | 0.008 | 0.014 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.034 | 0.033 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.014 | 0.015 |
| Research integrity | 0.028 | 0.033 |
| Insufficient payload (model declined to judge) | 0.054 | 0.042 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".