Publication of confirmatory studies required by Health Canada for drugs approved under a Notice of Compliance with conditions: a cohort study
Bibliographic record
Abstract
Background: Health Canada approves drugs based on limited data (Notice of Compliance with conditions [NOC/c]) and then requires companies to conduct confirmatory studies to validate the drugs9 efficacy/effectiveness. The current investigation was carried out to determine whether these confirmatory studies are eventually published and are available to health care practitioners. Methods: A list of drugs for which the confirmatory studies had been completed from 1998 to Sept. 30, 2014 was created from 2 published articles that listed NOCs/c and investigated whether they had been fulfilled, the NOC database and the NOC/c Web site. The confirmatory studies for these drugs were determined from Qualifying Notices, agreements between Health Canada and the drug companies. Possible publications from these studies were identified through a Web search, and companies were asked to confirm these publications. The time in days between fulfillment of the NOC/c and publication of the studies was calculated. Results: There were 58 distinct confirmatory studies for 24 products made by 14 different companies. Eleven companies responded and identified 29 unique publications that reported on 31 studies. One company did not confirm a publication that was subsequently independently identified. Three companies did not respond, and in these cases another 18 publications were independently identified for an additional 19 studies. No publications were found for 7 studies. Thirty-one publications appeared a mean of 610 days before the NOC/c was fulfilled, and 17 appeared a mean of 572 days after fulfillment of the NOC/c. Interpretation: Eighty-eight percent of the confirmatory studies were eventually published. Health Canada and drug manufacturers should take steps to ensure that knowledge about these publications is available to health care practitioners.
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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 | 0.070 | 0.214 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".