The fragility of randomized placebo‐controlled trials for irritable bowel syndrome
Bibliographic record
Abstract
BACKGROUND: The fragility index (FI) represents the number of participants whose status in a trial would have to change from a non-event (not experiencing the primary endpoint) to an event (experiencing the primary endpoint) in order to turn a statistically significant result into a non-significant result. We sought to evaluate the fragility indices of irritable bowel syndrome [IBS-mixed (IBS-M), IBS-constipation (IBS-C), & IBS-diarrhea (IBS-D)] trials. METHODS: Irritable bowel syndrome trials published in high-impact journals were identified from Medline. Trials had to be in adults, randomized, parallel-armed, with at least one statistically significant binary outcome, and an achieved primary endpoint of therapeutic efficacy. FI and correlation coefficients were calculated, and regression modeling used to identify predictors of a high FI. KEY RESULTS: Twelve trials were analyzed with a median FI of 6 (range: 0-38). Median sample size in all trials was 366 (range: 44-856). Trial publication year (p = 0.71), journal impact factor (p = 0.52), duration of study (p = 0.12), and number need to treat [NNT] (p = 0.29) were not predictive of a high FI. While a lower p-value correlated with a higher FI (p = 0.039), no correlation was noted between FI and impact factor (R = -0.20, p = 0.52), trial publication year (R = 0.12, p = 0.71), duration of trial (R = -0.46, p = 0.13), NNT (R = -0.34, p = 0.29), and sample size (R = 0.23, p = 0.5). The highest FI was in a Ramosetron trial (FI = 30) for IBS-D. CONCLUSION & INFERENCES: A median of six participants is needed to nullify results in the included IBS trials suggesting how easily statistical significance based on a threshold p-value may be overturned.
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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 | 0.511 | 0.729 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".