Reporting of financial conflicts of interest in clinical practice guidelines: a case study analysis of guidelines from the Canadian Medical Association Infobase
Bibliographic record
Abstract
BACKGROUND: Clinical practice guidelines are widely distributed by medical associations and relied upon by physicians for the best available clinical evidence. International findings report that financial conflicts of interest (FCOI) with drug companies may influence drug recommendations and are common among guideline authors. There is no comparable study on exclusively Canadian guidelines; therefore, we provide a case study of authors' FCOI declarations in guidelines from the Canadian Medical Association (CMA) Infobase. We also assess the financial relationships between guideline-affiliated organizations and drug companies. METHODS: Using a population approach, we extracted first-line drug recommendations and authors' FCOI disclosures in guidelines from the CMA Infobase. We contacted the corresponding authors on guidelines when FCOI disclosures were missing for some or all authors. We also extracted guideline-affiliated organizations and searched each of their websites to determine if they had financial relationships with drug companies. RESULTS: We analyzed 350 authors from 28 guidelines. Authors were named on one, two, or three guidelines, yielding 400 FCOI statements. In 75.0 % of guidelines at least one author, and in 21.4 % of guidelines all authors, disclosed FCOI with drug companies. In 54.0 % of guidelines at least one author, and in 28.6 % of guidelines over half of the authors, disclosed FCOI with manufacturers of drugs that they recommended. Twenty of 48 authors on multiple guidelines reported different FCOI in their disclosures. Eight guidelines identified affiliated organizations with financial relationships with manufacturers of drugs recommended in those guidelines. CONCLUSIONS: This is the first study to systematically describe FCOI disclosures by authors of Canadian guidelines and financial relationships between guideline-affiliated organizations and pharmaceutical companies. These financial relationships are common. Because authoritative value is assigned to guidelines distributed by medical associations, we encourage them to develop formal policies to limit the potential influence of FCOI on guideline recommendations.
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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 | 0.025 | 0.188 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.023 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".