Predictors of withdrawal of anticancer drug indications granted accelerated approval: a retrospective cohort study
Bibliographic record
Abstract
Background: The accelerated approval pathway allows the FDA to approve drugs for serious conditions based on promising surrogate measures, with confirmatory studies required later. If subsequent testing shows an unfavorable benefit-risk profile, the indication may be withdrawn. This study aimed to identify factors associated with the withdrawal of drug indications following accelerated approval. Methods: In this retrospective cohort study, we identified FDA-approved drugs for solid and hematologic cancers from 1992 to 2022 and extracted factors present at the time of accelerated approval, including pivotal trial characteristics, outcomes, and confirmatory study initiation timing from drug labels and published reports. Clinical benefit was assessed using the European Society of Medical Oncology-Magnitude of Clinical Benefit Scale (ESMO-MCBS), with high benefit as A-B/4-5 and low as C/≤2. Multivariable logistic regression identified factors associated with drug indication withdrawal. Findings: Among 167 accelerated approval indications for 113 anticancer drugs, by August 2024, 102 (61%) had been converted to regular approval, 31 (19%) were withdrawn, and the remaining 34 (20%) were ongoing accelerated approvals. Of the 133 indications that were either converted or withdrawn, 52 (39%) were approvals for hematologic cancer drugs, and 41 (31%) supported genome-targeted drug approvals. Among 83 eligible indications, 46 (55%) were granted Breakthrough Therapy designation. In the 133 pivotal trials, 112 (84%) used response rate as the primary endpoint, and 66% (86/130) offered low clinical benefit on the ESMO-MCBS. In multivariable analysis, Breakthrough Therapy designations (OR 0.26; 95% CI, 0.10-0.75; p = 0.01) and indications for genome-targeted therapies (OR 0.26; 95% CI, 0.08-0.80; p = 0.02) were associated with lower withdrawal rates. Higher withdrawal rates were associated with low ESMO-MCBS scores (OR, 4.63; 95% CI, 1.50-14.33; p = 0.008). Interpretation: Accelerated approvals based on early data suggesting limited clinical benefit tend to have higher withdrawal rates, whereas therapies with Breakthrough Therapy designation and genome-targeted mechanisms are more likely to validate clinical benefits and achieve regular approval. Patients and healthcare providers should consider these factors when evaluating whether to use therapies granted accelerated approval. Funding: Alfonso Martín Escudero Foundation (to AT) and Arnold Ventures, the Commonwealth Fund, and Kaiser Permanente Institute for Health Policy Research (to ASK).
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".