Clinical trial design in adult reflux disease: a methodological workshop
Bibliographic record
Abstract
BACKGROUND: The development of well-tolerated acid suppressant drugs has stimulated substantial growth in the number of trials assessing therapy options for gastro-oesophageal reflux disease (GERD). AIM: To develop consensus statements to inform clinical trial design in adult patients with GERD. METHODS: Draft statements were developed employing a systematic literature review. A modified Delphi process including three rounds of voting was used to reach consensus. Between voting, statements were revised based on feedback from the Working Group and additional literature reviews. The final vote was at a face-to-face meeting that included discussion time. Voting was conducted using a six-point scale. RESULTS: At the last vote, 93% of the final 102 statements achieved consensus (defined a priori as being supported by >or=75% of the votes). The Working Group strongly supported the development of validated patient-reported outcome instruments. Symptom assessments carried out by the investigator were considered unacceptable. There was agreement that exclusion from clinical trials should be minimized to improve generalizability, that prospective evaluation ideally requires electronic timed/dated methods and that endoscopists should be blinded to patient symptom status. CONCLUSIONS: Implementation of the consensus statements will improve the quality and comparability of trials, and make them compatible with regulatory requirements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.754 | 0.672 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".