Source of funding, conflict of interest (COI), and the interpretation of cancer clinical trials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
6530 Background: Concern exists that industry sponsorship and financial relationships between investigators and drug companies may bias clinical cancer research. Our objective was to determine whether funding or authors' COI are associated with interpreting cancer clinical trials in more positive light. Methods: We reviewed phase II and randomized clinical trials (RCT) of anticancer and supportive care drugs published in 5 clinical cancer journals in a one-year period. We collected information on study design, source of funding, COI disclosure and results of primary endpoints (EP). Each concluding statement in the articles′s abstracts were independently rated by two reviewers (blinded to other study information) with respect to level of enthusiasm for the experimental agent using a 5-point scale ( Table 1 ). Summary statistics and logistic regression were used to describe the results. Results: 213 articles met inclusion criteria: 124 phase II and 89 RCT. Approximately 40% were funded by industry, at least one COI was declared in 35% of articles. Among 130/213 (61%) articles with clearly positive conclusions, the proportion of articles with highly positive conclusions was 61% in articles that declared COI vs. 40% in articles with no COI (p=0.017, CMH, adjusted for study result). In a stepwise logistic regression with journal, funding, study type, study result, and COI only COI remained significant (OR=2.4, 95%CI 1.2–5.0, P=0.017). While all articles with a negative conclusion had a negative primary EP, 21 articles with clearly positive conclusions had a negative primary EP. The most common reasons for such finding were: positive secondary EP (6 studies), experimental agent had better toxicity profile (5), non-statistically significant difference in favour of experimental agent (4). Conclusion: COI is associated with highly positive conclusions that use superlatives to promote the experimental arm No significant financial relationships to disclose. [Table: see text]
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.
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 | 0.299 | 0.373 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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