Recommendations for progression criteria during external randomised pilot trial design, conduct, analysis and reporting
Bibliographic record
Abstract
BACKGROUND: External randomised pilot trials aim to assess whether a future definitive Randomised Controlled Trial (RCT) is feasible. Prespecified progression criteria help guide the interpretation of pilot trial findings to decide whether, and how, a definitive RCT should be conducted. This commentary presents a set of proposed recommendations for progression criteria to guide researchers when (i) designing, (ii) conducting, (iii) analysing and (iv) reporting external randomised pilot trials. METHODS: Recommendations were developed following a mixed methods approach. This involved (i) a methodological review of pilot trial publications, (ii) a cross-sectional study of pilot trial research funding applications, (iii) qualitative interviews with pilot trial researchers and (iv) a survey of corresponding authors of identified pilot trial publications. Initial recommendations were refined following two consultation stakeholder workshops held in July 2022. Recommendations for progression criteria for external randomised pilot trials: i. DESIGN: consider progression criteria from the earliest opportunity; map progression criteria to feasibility objectives; consider quantitative and qualitative interpretations of feasibility; provide justification; develop guidelines rather than rules; seek input from relevant stakeholders. ii. Conduct: regularly monitor pilot trial data against progression criteria. iii. ANALYSIS: avoid considering each progression criterion in isolation; engage in discussion with relevant stakeholders; consider context and other factors external to the pilot trial; consider feasibility (can we?) and progression (will we?). iv. Reporting: we propose a reporting checklist in relation to progression criteria and recommend reporting in a table format for clarity. CONCLUSION: These recommendations provide a helpful resource for researchers to consider progression criteria at different stages of external randomised pilot trials. We have produced a simple infographic tool to summarise these recommendations for researchers to refer to. Further research is needed to evaluate whether these proposed recommendations should inform future development, or update, of established guidelines for the design, conduct, analysis and reporting of external randomised pilot trials.
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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 | 0.798 | 0.935 |
| Meta-epidemiology (narrow) | 0.009 | 0.013 |
| Meta-epidemiology (broad) | 0.015 | 0.034 |
| Bibliometrics | 0.027 | 0.028 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.034 | 0.041 |
| Open science | 0.024 | 0.018 |
| Research integrity | 0.056 | 0.064 |
| Insufficient payload (model declined to judge) | 0.019 | 0.028 |
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".