Discrepancies between pre-specified and reported primary outcomes: A cross-sectional analysis of randomized controlled trials in gastroenterology and hepatology journals
Bibliographic record
Abstract
BACKGROUND: Previous research has raised concerns regarding inconsistencies between reported and pre-specified outcomes in randomized controlled trials (RCTs) across various biomedical disciplines. However, studies examining whether similar discrepancies exist in RCTs focusing on gastrointestinal and liver diseases are limited. This study aimed to assess the extent of discrepancies between registered and published primary outcomes in RCTs featured in journals specializing in gastroenterology and hepatology. METHODS: We retrospectively retrieved RCTs published between January 1, 2017 and December 31, 2021 in the top three journals from each quartile ranking of the 2020 Journal Citation Reports within the "Gastroenterology and Hepatology" subcategory. We extracted data on trial characteristics, registration details, and pre-specified versus published primary outcomes. Pre-specified primary outcomes were retrieved from the World Health Organization's International Clinical Trials Registry Platform. Only trials reporting specific primary outcomes were included in analyzing primary outcome discrepancies. We also assessed whether there was a potential reporting bias that deemed to favor statistically significant outcomes. Statistical analyses included chi-square tests, Fisher's exact tests, univariate analyses, and logistic regression. RESULTS: Of 362 articles identified, 312 (86.2%) were registered, and 79.8% of the registrations (249 out of 312) were prospective. Among the 285 trials reporting primary outcomes, 76 (26.7%) exhibited at least one discrepancy between registered and published primary outcomes. The most common discrepancies included different assessment times for the primary outcome (n = 32, 42.1%), omitting the registered primary outcome in publications (n = 21, 27.6%), and reporting the registered secondary outcomes as primary outcomes (n = 13, 17.1%). Univariate analyses revealed that primary outcome discrepancies were lower in the publication year 2020 compared to year 2021 (OR = 0.267, 95% CI: 0.101, 0.706, p = 0.008). Among the 76 studies with primary outcome discrepancies, 20 (26.3%) studies were retrospectively registered, and 32 (57.1%) of the prospectively registered trials with primary outcome discrepancies showed statistically significant results. However, no significant differences were found between journal quartiles regarding primary outcome consistency and potential reporting bias (p = 0.14 and p = 0.28, respectively). CONCLUSIONS: This study highlights the disparities between registered and published primary outcomes in RCTs within gastroenterology and hepatology journals. Attention to factors such as the timing of primary outcome assessments in published trials and the consistency between registered and published primary outcomes is crucial. Enhanced scrutiny from journal editors and peer reviewers during the review process is necessary to ensure the reliability of gastrointestinal and hepatic 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 | 0.324 | 0.616 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.019 | 0.022 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".