Clinical benefit and cost of breakthrough cancer drugs approved by the US Food and Drug Administration
Bibliographic record
Abstract
BACKGROUND: The clinical benefit and pricing of breakthrough-designated cancer drugs are uncertain. This study compares the magnitude of the clinical benefit and monthly price of new and supplemental breakthrough-designated and non-breakthrough-designated cancer drug approvals. METHODS: A cross-sectional cohort comprised approvals of cancer drugs for solid tumors from July 2012 to December 2017. For each indication, the clinical benefit from the pivotal trials was scored via validated frameworks: the American Society of Clinical Oncology Value Framework (ASCO-VF), the American Society of Clinical Oncology Cancer Research Committee (ASCO-CRC), the European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS), and the National Comprehensive Cancer Network (NCCN) Evidence Blocks. A high clinical benefit was defined as scores ≥ 45 for the ASCO-VF, overall survival gains ≥ 2.5 months or progression-free survival gains ≥ 3 months for all cancer types for the ASCO-CRC criteria, a grade of A or B for trials of curative intent and a grade of 4 or 5 for trials of noncurative intent for the ESMO-MCBS, and scores of 4 and 5 and a combined score ≥ 16 for the NCCN Evidence Blocks. Monthly Medicare drug prices were calculated with Medicare prices and DrugAbacus. RESULTS: This study identified 106 trials supporting approval of 52 drugs for 96 indications. Forty percent of these indications received the breakthrough designation. Among the included trials, 33 (43%), 46 (73%), 35 (34%), and 67 (69%) met the thresholds established by the ASCO-VF, ASCO-CRC, ESMO-MCBS, and NCCN, respectively. In the metastatic setting, there were higher odds of clinically meaningful grades in trials supporting breakthrough drugs with the ASCO-VF (odds ratio [OR], 3.69; P = .022) and the NCCN Evidence Blocks (OR, 5.80; P = .003) but not with the ASCO-CRC (OR, 3.54; P = .11) or version 1.1 (v1.1) of the ESMO-MCBS (OR, 1.22; P = .70). The median costs of breakthrough therapy drugs were significantly higher than those of nonbreakthrough therapies (P = .001). CONCLUSIONS: In advanced solid cancers, drugs that received the breakthrough therapy designation were more likely than nonbreakthrough therapy drugs to be scored as providing a high clinical benefit with the ASCO-VF and the NCCN Evidence Blocks but not with the ESMO-MCBS v1.1 or the ASCO-CRC scale.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".