MétaCan
Menu
Back to cohort

Access to initial and subsequent indications of new oncology drugs: A US-Canada comparison.

2025· article· en· W4410807268 on OpenAlexaboutno aff
Julie A. Patterson, Rayan Salih, Tyler D. Wagner, Jonathan D. Campbell

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOncologyInternal medicineClinical OncologyFamily medicineCancer

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.012
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.192
GPT teacher head0.471
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicEconomic and Financial Impacts of CancerFrench-language works237,207