Clinical Value of Molecular Targets and FDA-Approved Genome-Targeted Cancer Therapies
Bibliographic record
Abstract
Importance: The number of new genome-targeted cancer drugs has increased, offering the possibility of personalized therapy, often at a very high cost. Objective: To assess the validity of molecular targets and therapeutic benefits of US Food and Drug Administration-approved genome-targeted cancer drugs based on the outcomes of their corresponding pivotal clinical trials. Design and Settings: In this cohort study, all genome-targeted cancer drugs that were FDA-approved between January 1, 2015, and December 31, 2022, were analyzed. From FDA drug labels and trial reports, key characteristics of pivotal trials were extracted, including the outcomes assessed. Main Outcomes and Measures: The strength of evidence supporting molecular targetability was assessed using the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of Molecular Targets (ESCAT). Clinical benefit for their approved indications was evaluated using the ESMO-Magnitude of Clinical Benefit Scale (ESMO-MCBS). Substantial clinical benefit was defined as a grade of A or B for curative intent and 4 or 5 for noncurative intent. Molecular targets qualifying for ESCAT category level I-A and I-B associated with substantial clinical benefit by ESMO-MCBS were rated as high-benefit genomic-based cancer treatments. Results: A total of 50 molecular-targeted drugs covering 84 indications were analyzed. Forty-five indications (54%) were approved based on phase 1 or phase 2 pivotal trials, 45 (54%) were supported by single-arm pivotal trials, and 48 (57%) were approved on the basis of subgroup analyses. By each indication, 46 of 84 primary end points (55%) were overall response rate (median [IQR] overall response rate, 57% [40%-69%]; median [IQR] duration of response, 11.1 [9.2-19.8] months). Among the 84 pivotal trials supporting these 84 indications, 38 trials (45%) had I-A ESCAT targetability, and 32 (38%) had I-B targetability. Overall, 24 of 84 trials (29%) demonstrated substantial clinical benefit via ESMO-MCBS. Combining these ratings, 24 of 84 indications (29%) were associated with high-benefit genomic-based cancer treatments. Conclusions and Relevance: The results of this cohort study demonstrate that among recently approved molecular-targeted cancer therapies, fewer than one-third demonstrated substantial patient benefits at approval. Benefit frameworks such as ESMO-MCBS and ESCAT can help physicians, patients, and payers identify therapies with the greatest clinical potential.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".