Randomised clinical trial: Efficacy and safety of <scp>on‐demand</scp> vonoprazan versus placebo for non‐erosive reflux disease
Bibliographic record
Abstract
BACKGROUND: Non-erosive reflux disease (NERD) symptoms are often episodic, making on-demand treatment an attractive treatment approach. AIMS: We compared the efficacy and safety of on-demand vonoprazan versus placebo in patients with NERD. METHODS: Patients with NERD, defined as heartburn for ≥6 months and for ≥4/7 consecutive days with normal endoscopy, received once-daily vonoprazan 20 mg during a 4-week run-in period. Patients without heartburn during the last 7 days and with ≥80% study drug and diary compliance were randomised 1:1:1:1 to vonoprazan 10, 20, 40 mg or placebo on-demand for 6 weeks. The primary endpoint was the percentage of evaluable heartburn episodes completely relieved within 3 h of on-demand dosing and sustained for 24 h. RESULTS: Of 458 patients in the run-in period, 207 entered the on-demand period. In the vonoprazan 10 mg group, 56.0% (201/359) of evaluable heartburn episodes met the criteria for complete and sustained relief; 60.6% (198/327) in the 20 mg group; and 70.0% (226/323) in the 40 mg group, compared with 27.3% (101/370) in the placebo group (p < 0.0001 versus placebo for each vonoprazan group). By 1 h post-dose, vonoprazan was associated with complete relief of significantly more heartburn episodes compared with placebo. No serious treatment-emergent adverse events were reported. CONCLUSION: On-demand vonoprazan may be a potential alternative to continued daily acid suppression therapy for the relief of episodic heartburn in patients with NERD. CLINICALTRIALS: gov: NCT04799158.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".