Postmarket safety of drugs approved by Health Canada on the basis of clinical and surrogate outcomes: a cohort study
Bibliographic record
Abstract
BACKGROUND: Health Canada approves drugs on the basis of evidence from clinical trials using clinical or surrogate outcomes. This study compares the postmarket safety of these 2 groups of drugs. METHODS: Information about whether clinical or surrogate outcomes were used and the date of market approval were obtained from Health Canada's Summary Basis of Decision documents issued from Jan. 1, 2005, to Dec. 31, 2014. Safety warnings and the dates they were issued were identified through advisories on the MedEffect Canada website. Kaplan-Meier survival curves were calculated to determine the likelihood that drugs in the clinical and surrogate outcome groups would receive a serious safety warning. The time from market authorization to first serious safety warning was compared for the 2 groups of drugs. RESULTS: A total of 124 drugs were approved by Health Canada using clinical outcomes and 114 using surrogate outcomes. Kaplan-Meier curves did not differ between the 2 groups (p < 0.9). The median time from market authorization to first serious safety warning was 722 days in the clinical outcome group and 818 days in the surrogate outcome group (difference 96 days, 95% confidence interval -295 to 425). INTERPRETATION: We found no statistically significant difference in postmarket safety between drugs approved using clinical outcomes and those approved using surrogate outcomes. Because drugs in the surrogate outcome group are approved before their benefit:harm ratio is fully established, these drugs should be used with caution until their clinical benefits are better understood.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".