Abstract PD10-06: Clinical benefit of breast cancer drugs approved by the United States Food and Drug Administration
Bibliographic record
Abstract
Abstract Background: The American Society of Clinical Oncology Cancer Research Committee (ASCO-CRC), the ASCO Value Framework Net Health Benefit score version 2 (ASCO-NHB v2), and the European Society for Medical Oncology-Magnitude of Clinical Benefit Scale version 1.1 (ESMO-MCBS v1.1) are validated tools which quantify the clinical benefit for cancer drugs. Here, we assess the magnitude of clinical benefit of clinical trials supporting breast cancer drug approval by the United States Food and Drug Administration (FDA). Methods: We searched the Drugs@FDA website for breast cancer drug approvals from January 1, 2006 to June 30, 2019. Drug labels and reports of registration trials were reviewed and study characteristics, efficacy, toxicity and quality of life (QoL) outcomes were collected. For each indication, we scored clinical benefit from pivotal trials using the ASCO-CRC for non-curative trials and using the ASCO-NHB v2 and the ESMO-MCBS v1.1 for curative and non-curative intent trials. Substantial clinical benefit was defined as: overall survival (OS) gains of 2.5 or more months and progression-free survival gains of 3 or more months for all cancer types for the ASCO-CRC criteria; pragmatic threshold scores of 45 or greater for the ASCO-NHB v2; and grade of A or B for trials of curative intent and 4 or 5 for those of non-curative intent using ESMO-MCBS v1.1. Results: We identified 28 pivotal trials supporting the approval of 18 individual drugs for 24 indications. Among the 28 trials, 6 (21%) were in the curative setting and 22 (79%) in the palliative setting. At the time of approval, only 2 trials (7%) reported improvement in OS and only 4 trials (14%) a significant improvement in QoL. ASCO-CRC, ASCO-NHB v2 and ESMO-MCBS v1.1 scores were applied in the palliative setting to 19, 20 and 22 trials respectively, and ASCO-VF and ESMO-MCBS v1.1 in the curative setting in 4 and 5 trials respectively. Among included trials in advanced disease, 15 (79%), 9 (45%) and 5 (23%), trials met the thresholds established by the ASCO-CRC, ASCO-NHB v2 and ESMO-MCBS v1.1 respectively. Among trials with curative intent, 1 (25%) and 4 (80%) trials met the thresholds established by the ASCO-NHB v2 and ESMO-MCBS v1.1 respectively. Conclusion: In patients with metastatic breast cancer, most FDA approval trials do not meet the ASCO-NHB v2 and ESMO-MCBS v1.1 thresholds for substantial clinical benefit. Although most palliative trials reported a substantial clinical benefit according ASCO-CRC framework only 2 of them (7%) supported drug approvals based on an OS benefit. In patients with early breast cancer, low agreement observed between the ASCO-NHB v2 and ESMO-MCBS v1.1 suggest that the respective frameworks may require additional refinement to accurately capture substantial clinical benefit in the curative setting. Citation Format: J. Carlos Tapia, Consolación Molto, Aida Bujosa, Arnoud J Templeton, Agustí Barnadas, Eithan Amir, Ariadna Tibau. Clinical benefit of breast cancer drugs approved by the United States Food and Drug Administration [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD10-06.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".