Multicenter, double-blind, placebo-controlled trial of seviprotimut-L polyvalent melanoma vaccine in patients with post-resection melanoma at high risk of recurrence
Bibliographic record
Abstract
BACKGROUND: Most patients with advanced melanomas relapse after checkpoint blockade therapy. Thus, immunotherapies are needed that can be applied safely early, in the adjuvant setting. Seviprotimut-L is a vaccine containing human melanoma antigens, plus alum. To assess the efficacy of seviprotimut-L, the Melanoma Antigen Vaccine Immunotherapy Study (MAVIS) was initiated as a three-part multicenter, double-blind, placebo-controlled phase III trial. Results from part B1 are reported here. METHODS: Patients with AJCC V.7 stage IIB-III cutaneous melanoma after resection were randomized 2:1, with stage stratification (IIB/C, IIIA, IIIB/C), to seviprotimut-L 40 mcg or placebo. Recurrence-free survival (RFS) was the primary endpoint. For an hypothesized HR of 0.625, one-sided alpha of 0.10, and power 80%, target enrollment was 325 patients. RESULTS: For randomized patients (n=347), arms were well-balanced, and treatment-emergent adverse events were similar for seviprotimut-L and placebo. For the primary intent-to-treat endpoint of RFS, the estimated HR was 0.881 (95% CI: 0.629 to 1.233), with stratified logrank p=0.46. However, estimated HRs were not uniform over the stage randomized strata, with HRs (95% CIs) for stages IIB/IIC, IIIA, IIIB/IIIC of 0.67 (95% CI: 0.37 to 1.19), 0.72 (95% CI: 0.35 to 1.50), and 1.19 (95% CI: 0.72 to 1.97), respectively. In the stage IIB/IIC stratum, the effect on RFS was greatest for patients <60 years old (HR=0.324 (95% CI: 0.121 to 0.864)) and those with ulcerated primary melanomas (HR=0.493 (95% CI: 0.255 to 0.952)). CONCLUSIONS: Seviprotimut-L is very well tolerated. Exploratory efficacy model estimation supports further study in stage IIB/IIC patients, especially younger patients and those with ulcerated melanomas. TRIAL REGISTRATION NUMBER: NCT01546571.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".