Adjuvant Nivolumab versus Ipilimumab in Resected Stage III/IV Melanoma: 5-Year Efficacy and Biomarker Results from CheckMate 238
Bibliographic record
Abstract
PURPOSE: In the phase III CheckMate 238 study, adjuvant nivolumab significantly improved recurrence-free survival (RFS) and distant metastasis-free survival versus ipilimumab in patients with resected stage IIIB-C or stage IV melanoma, with benefit sustained at 4 years. We report updated 5-year efficacy and biomarker findings. PATIENTS AND METHODS: Patients with resected stage IIIB-C/IV melanoma were stratified by stage and baseline programmed death cell ligand 1 (PD-L1) expression and received nivolumab 3 mg/kg every 2 weeks or ipilimumab 10 mg/kg every 3 weeks for four doses and then every 12 weeks, both intravenously for 1 year until disease recurrence, unacceptable toxicity, or withdrawal of consent. The primary endpoint was RFS. RESULTS: At a minimum follow-up of 62 months, RFS with nivolumab remained superior to ipilimumab (HR = 0.72; 95% confidence interval, 0.60-0.86; 5-year rates of 50% vs. 39%). Five-year distant metastasis-free survival (DMFS) rates were 58% with nivolumab versus 51% with ipilimumab. Five-year overall survival (OS) rates were 76% with nivolumab and 72% with ipilimumab (75% data maturity: 228 of 302 planned events). Higher levels of tumor mutational burden (TMB), tumor PD-L1, intratumoral CD8+ T cells and IFNγ-associated gene expression signature, and lower levels of peripheral serum C-reactive protein were associated with improved RFS and OS with both nivolumab and ipilimumab, albeit with limited clinically meaningful predictive value. CONCLUSIONS: Nivolumab is a proven adjuvant treatment for resected melanoma at high risk of recurrence, with sustained, long-term improvement in RFS and DMFS compared with ipilimumab and high OS rates. Identification of additional biomarkers is needed to better predict treatment outcome. See related commentary by Augustin and Luke, p. 3253.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".