Adjuvant Pembrolizumab versus IFNα2b or Ipilimumab in Resected High-Risk Melanoma
Bibliographic record
Abstract
We conducted a randomized phase III trial to evaluate whether adjuvant pembrolizumab for one year (647 patients) improved recurrence-free survival (RFS) or overall survival (OS) in comparison with high-dose IFNα-2b for one year or ipilimumab for up to three years (654 patients), the approved standard-of-care adjuvant immunotherapies at the time of enrollment for patients with high-risk resected melanoma. At a median follow-up of 47.5 months, pembrolizumab was associated with significantly longer RFS than prior standard-of-care adjuvant immunotherapies [HR, 0.77; 99.62% confidence interval (CI), 0.59-0.99; P = 0.002]. There was no statistically significant association with OS among all patients (HR, 0.82; 96.3% CI, 0.61-1.09; P = 0.15). Proportions of treatment-related adverse events of grades 3 to 5 were 19.5% with pembrolizumab, 71.2% with IFNα-2b, and 49.2% with ipilimumab. Therefore, adjuvant pembrolizumab significantly improved RFS but not OS compared with the prior standard-of-care immunotherapies for patients with high-risk resected melanoma. SIGNIFICANCE: Adjuvant PD-1 blockade therapy decreases the rates of recurrence, but not survival, in patients with surgically resectable melanoma, substituting the prior standard-of-care immunotherapies for this cancer. See related commentary by Smithy and Shoushtari, p. 599. This article is highlighted in the In This Issue feature, p. 587.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".