Developing a guideline for clinical trial protocol content: Delphi consensus survey
Bibliographic record
Abstract
BACKGROUND: Recent evidence has highlighted deficiencies in clinical trial protocols, having implications for many groups. Existing guidelines for randomized clinical trial (RCT) protocol content vary substantially and most do not describe systematic methodology for their development. As one of three prespecified steps for the systematic development of a guideline for trial protocol content, the objective of this study was to conduct a three-round Delphi consensus survey to develop and refine minimum content for RCT protocols. METHODS: Panellists were identified using a multistep iterative approach, met prespecified minimum criteria and represented key stakeholders who develop or use clinical trial protocols. They were asked to rate concepts for importance in a minimum set of items for RCT protocols. The main outcome measures were degree of importance (scale of 1 to 10; higher scores indicating higher importance) and level of consensus for items. Results were presented as medians, interquartile ranges, counts and percentages. RESULTS: Ninety-six expert panellists participated in the Delphi consensus survey including trial investigators, methodologists, research ethics board members, funders, industry, regulators and journal editors. Response rates were between 88 and 93% per round. Overall, panellists rated 63 of 88 concepts of high importance (of which 50 had a 25th percentile rating of 8 or greater), 13 of moderate importance (median 6 or 7) and 12 of low importance (median less than or equal to 5) for minimum trial protocol content. General and item-specific comments and subgroup results provided valuable insight for further discussions. CONCLUSIONS: This Delphi process achieved consensus from a large panel of experts from diverse stakeholder groups on essential content for RCT protocols. It also highlights areas of divergence. These results, complemented by other empirical research and consensus meetings, are helping guide the development of a guideline for protocol content.
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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 | 0.493 | 0.450 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".