Phase II Study of Sunitinib in Tumors With <i>c-KIT</i> Mutations: Results From the NCI MATCH ECOG-ACRIN Trial (EAY131) Subprotocol V
Bibliographic record
Abstract
PURPOSE The NCI-MATCH study is a tumor-agnostic platform trial enrolling patients to targeted therapies on the basis of genomic alterations. Subprotocol V investigated sunitinib in patients with tumors harboring c - KIT mutations. METHODS EAY131-V, is an open-label, single-arm, phase II study. Eligible patients had malignancies containing somatic c-KIT mutation on exons 9, 11, 13, or 14. Exclusions were mutations on exons 17 and 18, gastrointestinal stromal tumors, renal cell carcinoma, and pancreatic neuroendocrine tumors. Patients received sunitinib 50 mg orally once daily for 4 weeks with 2-week rest per cycle, until disease progression or unacceptable toxicity. Primary end point was objective response rate (ORR); secondary end points were progression-free survival (PFS) at 6 months, PFS, overall survival, and toxicities. RESULTS Between November 1, 2016, and May 21, 2020, 10 patients were enrolled and nine were eligible and started treatment. The median age was 62 years (range, 30-76), 77.8% received two previous lines of systemic therapy, and 22.2% received >3 lines. The most common histology was melanoma (44%) and then squamous cell carcinoma of the lung or thymus (33%). There were two partial responses with an ORR of 22.2% (90% CI, 4.1 to 55) and stable disease in 44%. All patients demonstrated tumor shrinkage of target lesions. The estimated 6-month PFS was 33.3% (90% CI, 15.4 to 72.4). Grade 3-4 toxicities occurred in five patients (55.6%). This arm was closed in 2022 on the basis of low accrual. Prevalence of eligible c-KIT mutations after screening 5,540 patients was 0.45%. CONCLUSION Sunitinib for c-KIT mutations did not meet the primary end point, but in this small sample size, a potential signal cannot be ruled out. Rate of eligible c-KIT mutations was low, affecting accrual to this arm.
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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 | 0.001 | 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 | 0.001 |
| 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".