A161 PREVALENCE OF FINANCIAL CONFLICTS OF INTEREST (FCOI) AMONG PROPENSITY-SCORE MATCHED RETROSPECTIVE STUDIES EVALUATING BIOLOGIC THERAPEUTICS FOR IBD
Bibliographic record
Abstract
Abstract Background Inflammatory Bowel Disease (IBD) studies have commonly relied on real-world evidence to evaluate different therapies. An emerging idea has been the use of propensity score matching as a statistical method to account for baseline characteristics in IBD patients. In retrospective studies, propensity score matching of patients helps reduce treatment assignment bias and mimic the effects of randomization. Recently, propensity-score matching has become an important tool in IBD studies comparing biologic therapeutics. Biologic medications are among the highest-grossing drugs worldwide, and their pharmaceutical producers make considerable payments to physicians to market them. In spite of this, there is a lack of evidence examining the role of undue industry influence among propensity-score matched comparative studies evaluating biologic therapeutics for IBD. Aims Given the documented association between IBD biologics and FCOI, we hypothesize a high burden of FCOI in propensity-score matched studies. The aim of this study was to evaluate the prevalence of disclosed & undisclosed financial conflicts of Interest (FCOI) in propensity-score matched comparison studies evaluating biologics for IBD. Methods We developed & ran a librarian-reviewed systematic search on EMBASE, MEDLINE, and Cochrane Library databases for all propensity-score matched retrospective studies comparing biologics for the treatment of IBD. Full-text retrieval & screening was performed on all studies in duplicate. 16 articles were identified. Industry payments to authors were only considered FCOI if they were made by a company producing a biologic that was included in the comparison study. Disclosed FCOI were identified by authors’ interests disclosures in full-texts. Any undisclosed FCOI among US authors were identified using the Centre for Medicare and Medicaid Services (CMS) Open Payments Database, which collects industry payments to physicians. Results Based on a preliminary analysis of 16 studies, there was at least one author with a relevant FCOI in 14 (88%) of the 16 studies. 14 studies (88%) had at least one disclosed FCOI, while 6 studies (37.5%) had at least one undisclosed FCOI. Among studies with disclosed FCOI, a mean of 40.2% (SD = 23.4%) of authors/study reported FCOI. Among studies with undisclosed FCOI, a mean of 18.8% (SD = 7.0%) of authors/study reported FCOI. The total dollar value of FCOIs was $1,974,328.3. The median conflict dollar value was $5,576.6 (IQR: $321.6 to $36,394.9). Conclusions We found a high burden of undisclosed FCOI (37.5%) among authors of propensity-score matched studies evaluating IBD biologics. Given the potential for undue industry influence stemming from such payments, authors should ensure better transparency with industry relationships. Funding Agencies None
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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 | 0.043 | 0.182 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".