Access to initial and subsequent indications of new oncology drugs: A US-Canada comparison.
Bibliographic record
Abstract
e23048 Background: Timelines of regulatory and health technology assessment (HTA) submissions and decisions vary by country, impacting patient access to new drugs and subsequent indications. Research on international oncology drug access often focuses on one step towards access (e.g., regulatory approval) or initial indications. We compared the full access ‘funnel,’ including regulatory and HTA submissions and decisions, between the United States (US) and Canada for initial and subsequent indications in multi-indication oncology drugs. Methods: We recorded all oncology drugs with both initial and subsequent indications approved by the FDA from 2018-2023. US regulatory dates were obtained from Drugs@FDA. Canadian regulatory and HTA dates and decisions were extracted from NAVLIN®, Health Canada (HC), and the Canadian Agency for Drugs and Technologies in Health (CADTH; now Canada’s Drug Agency). We calculated the number of FDA-approved drug-indication pairs submitted, approved, and reimbursed in Canada, overall and by indication type (i.e., initial or subsequent). We estimated median (IQR) time from FDA approval (all FDA-approved oncology drugs are covered by Medicare) to patient access in Canada, indicated by the date of a “reimburse” recommendation or censoring (1/28/25). Results: A total of 25 oncology drugs had both an initial and subsequent indication approved by the FDA from 2018-2023, for a sample of 64 drug-indication pairs. Forty (62.5%, n = 40/64) drug-indication pairs were submitted to HC, including 80% (n = 20/25) of initial and 51.3% (n = 20/39) of subsequent indications. Of drug-indication pairs submitted to both agencies, 85% (n = 34/40) were submitted first to the FDA, including 95% (n = 19/20) of initial and 75% (n = 15/20) of subsequent indications. All indications submitted to HC were approved, and 90% (n = 36/40) were submitted to CADTH. Of those 36 drug-indication pairs, 86.1% (n = 31) received a recommendation to reimburse, including 76.5% (n = 13/17) of initial and 94.7% (n = 18/19) of subsequent indications. Overall, then, of FDA-approved initial and subsequent indications, 52% (n = 13/25) and 46.2% (n = 18/39), respectively, gained “reimburse” recommendations. The median time from US to Canadian access was 689 days overall (IQR: 435, 1311), 755 days (IQR: 509, 1846) for initial indications, and 588 days (IQR: 363, 1232) for subsequent indications. In drugs with “reimburse” recommendations, a median of 645 (IQR: 481, 750) and 328 (IQR: 153, 541) days elapsed between US and Canadian access to initial and subsequent indications, respectively. Conclusions: Access to new cancer drugs and their subsequent indications was higher in the US than Canada. FDA-approved initial indications were more often submitted to HC and given a “reimburse” recommendation by CADTH than subsequent indications. However, delays to approval and reimbursement were numerically longer for initial than subsequent indications.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".