Adjuvant nivolumab versus ipilimumab (CheckMate 238 trial): Reassessment of 4-year efficacy outcomes in patients with stage III melanoma per AJCC-8 staging criteria
Bibliographic record
Abstract
PURPOSE: Nivolumab was approved as adjuvant therapy for melanoma based on data from CheckMate 238, which enrolled patients per American Joint Committee on Cancer version 7 (AJCC-7) criteria. Here, we analyse long-term outcomes per AJCC-8 staging criteria compared with AJCC-7 results to inform clinical decisions for patients diagnosed per AJCC-8. PATIENTS AND METHODS: In a double-blind, phase 3 trial (NCT02388906), patients aged ≥15 years with resected, histologically confirmed AJCC-7 stage IIIB, IIIC, or IV melanoma were randomised to receive nivolumab 3 mg/kg every 2 weeks or ipilimumab 10 mg/kg every 3 weeks for 4 doses and then every 12 weeks, both intravenously ≤1 year. Recurrence-free survival (RFS) and distant metastasis-free survival (DMFS) were assessed in patients with stage III disease, per AJCC-7 and AJCC-8. RESULTS: Per AJCC-7 staging, 42.4% and 57.3% of patients were in substage IIIB and IIIC, respectively; per AJCC-8, 1.1%, 30.4%, 62.8%, and 5.0% were in IIIA, IIIB, IIIC, and IIID. After 4 years' minimum follow-up, the AJCC-7 superior efficacy of nivolumab over ipilimumab in patients with resected stage III melanoma was preserved per AJCC-8 analysis. No statistically significant difference in RFS between stage III substage hazard ratios was observed per AJCC-7 or -8 staging criteria (interaction test: AJCC-7, P = 0.8115; AJCC-8, P = 0.1051; P = 0.8392 ((AJCC-7) and P = 0.8678 (AJCC-8) for DMFS). CONCLUSIONS: CheckMate 238 4-year RFS and DMFS outcomes are consistent per AJCC-7 and AJCC-8 staging criteria. Outcome benefits can therefore be translated for patients diagnosed per AJCC-8.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".