Cancer Therapy Approval Timings, Review Speed, and Publication of Pivotal Registration Trials in the US and Europe, 2010-2019
Bibliographic record
Abstract
Importance: Ensuring patients have access to safe and efficacious medicines in a timely manner is an essential goal for regulatory agencies, one which has particular importance in oncology because of the substantial unmet need for new therapies. The 2 largest regulatory agencies, the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA), have pivotal global roles, and their recommendations and approvals are frequently followed by other national regulators. Objective: To compare market authorization dates for new oncology therapies approved in the US and Europe over the past decade and to examine and contrast the regulatory activities of the FDA and EMA in the approval of new cancer medicines. Design, Setting, and Participants: This cross-sectional study reviewed the FDA and EMA regulatory databases to identify new oncology therapies approved in both the US and Europe from 2010 to 2019, and characterization of the timings of regulatory activities. Statistical analysis was performed from January to April 2022. Main Outcomes and Measures: Regulatory approval date, review time, submission of market authorization application, accelerated approval or conditional marketing authorization status and proportion of approvals prior to peer-reviewed publication of pivotal trial results. Results: In total, 89 new concomitant oncology therapies were approved in the US and Europe from 2010 to 2019. The FDA approved 85 oncology therapies (95%) before European authorization and 4 therapies (5%) after. The median (IQR) delay in market authorization for new oncology therapies in Europe was 241 (150-370) days compared with the US. The median (IQR) review time was 200 (155-277) days for the FDA and 426 (358-480) days for the EMA. Sixty-four new licensing applications (72%) were submitted to the FDA first, compared with 21 (23%) to the EMA. Thirty-five oncology therapies (39%) were approved by the FDA prior to pivotal study publication, whereas only 8 (9%) by the EMA. Conclusion and Relevance: In this cross-sectional study, new oncology therapies were approved earlier in the US than Europe. The FDA received licensing applications sooner and had shorter review times. However, more therapies were approved prior to licensing study publication, leaving uncertainty for practitioners regarding clinical utility and safety of newly approved therapies.
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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 | 0.064 | 0.156 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".