Reporting of financial conflicts of interest by Canadian clinical practice guideline producers: a descriptive study
Bibliographic record
Abstract
BACKGROUND: The producers of clinical practice guidelines (CPGs) may not disclose industry funding in their CPGs. We reviewed Canadian national CPGs to examine the existence and disclosure of industry-related organizational funding in the CPGs, financial conflicts of interest of committee members and organizational procedures for managing financial conflicts of interest. METHODS: For this descriptive study, we searched the asset map of the Strategy for Patient-Oriented Research Evidence Alliance and the CPG Infobase for CPGs published between Jan. 1, 2016, and Nov. 30, 2018. Eligible guidelines had to have a national focus and either a first-line drug recommendation or a screening recommendation leading to drug treatment. One investigator reviewed all CPG titles to exclude those that were clearly ineligible. Two reviewers independently reviewed all remaining guidelines and extracted data. We analyzed the data descriptively. RESULTS: We included 21 CPGs: 3 from government-sponsored organizations, 9 from disease or condition interest groups and 9 from medical professional societies. None of the 3 government-sponsored organizations reported industry funding, and none of their committee members disclosed financial conflicts of interest. Among the 18 disease or condition interest groups and medical professional societies, 14 (93%) of the 15 that disclosed funding sources on websites (3 did not disclose) reported organizational funding from industry, but none disclosed this information in the CPGs; 12 (86%) of the 14 with conflict-of-interest disclosure statements in the CPG (4 did not include disclosures) had at least 1 committee member with a financial conflict (mean proportion of committee members with a conflict 56%); and for all 8 CPGs with identifiable chairs or cochairs (chairs or cochairs not reported for 10) at least 1 of these people had a financial conflict of interest. None of the guidelines described a plan to manage organizational financial conflicts of interest. INTERPRETATION: Canadian CPGs are vulnerable to industry influence through funding of producers of guidelines and through the financial conflicts of interest of committee members. The CPG producers that receive industry funding should disclose organizational financial conflicts in the CPGs, should engage independent oversight committees and should restrict voting on recommendations to guideline panelists who have no financial conflicts.
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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 | 0.024 | 0.174 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.023 | 0.035 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".