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.
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 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 | 0.041 | 0.117 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".