A comparison of the Food and Drug Administration’s and Health Canada’s regulatory decisions about failed confirmatory trials for oncology drugs: an observational study
Bibliographic record
Abstract
BACKGROUND: Oncology drugs are frequently approved on the basis of surrogate outcomes that require further trials to confirm the benefits, but at times these trials fail and regulators need to decide whether to withdraw approval for the indication and/or to remove the drug from the market. This study compares decisions by the Food and Drug Administration and Health Canada about oncology drugs that were approved using either Accelerated Approval (FDA) or Notice of Compliance with conditions (NOC/c, Health Canada) and that failed confirmatory trials. METHODS: Drug/indications approved by the FDA through its Accelerated Approval Pathway and that later failed confirmatory studies were identified from a published study and additional information on these drugs was collected from Drugs@FDA. Health Canada websites were searched on September 11, 2021 for the same group of drugs to determine if they were approved in Canada under the NOC/c pathway for the same indication as in the US. Information from both the FDA and Health Canada about these products was entered into an Excel spreadsheet. Decisions about whether to withdraw the drugs or remove the failed indication for the drug and requirements for confirmatory studies were compared. In addition, the dates of decisions by the two agencies were compared. RESULTS: Ten drug/indications were available for comparison. Regulatory decisions were similar in 4 cases, different in 1 case and could not be determined in the remaining 5, in 1 case because decisions were pending in both countries and in the other 4, because the NOC/c had not been fulfilled in Canada. The requirements for the confirmatory studies were similar in both countries. Decisions were made earlier in the United States. CONCLUSIONS: This study shows that decisions made by Health Canada and the FDA about whether to withdraw a drug or remove a failed indication when drug/indications fail a confirmatory trial are usually similar, although the sample size on which this conclusion is made is small. The clinical implications of these similarities and differences should be explored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".