The Impact of Industry Funding on Randomized Controlled Trials of Biologic Therapies
Why this work is in the frame
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Bibliographic record
Abstract
Background: There has been substantial interest from the pharmaceutical industry to study and develop new biologic agents. Previous studies outside of the biologics field have demonstrated that industry funding has the potential to impact the design and findings of clinical trials. The objective of this study was to evaluate the impact of industry funding on randomized controlled trials (RCTs) that investigated the efficacy of biologic therapies. Methods: A review of all RCTs involving biologic therapies in top impact factor medical journals from January 2018 to December 2020 was performed. The relationship between industry funding and the presence of statistically significant primary outcomes and the use of active comparators were analyzed. Results: Among the 157 RCTs included, 120 (76%) were industry funded and 37 (24%) declared no industry funding. Industry-funded studies were significantly more likely to report a statistically significant positive primary outcome compared to studies without industry funding (85% vs. 67%, χ2 = 5.867, p = 0.015) and were significantly more likely to utilize placebo or no comparator than non-industry-funded trials (78% vs. 49%, χ2 = 4.430, p = 0.035). Conclusions: Industry-funded trials investigating biologic therapies are more likely to yield statistically significant positive outcomes and use placebo comparators when compared to non-industry-funded biologic therapy trials in high-impact medical journals.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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 it