Long-term outcomes among patients who respond within the first year to nivolumab plus ipilimumab or nivolumab monotherapy: A pooled analysis in 935 patients
Bibliographic record
Abstract
PURPOSE: To investigate the predictive value of RECIST response within 3, 6, or 12 months on long-term survival, and explore differences between nivolumab+ipilimumab and nivolumab monotherapy, we analyzed pooled 5-year data of 935 responder and non-responder patients at various time points after treatment initiation in CheckMate 069, 066, and 067 studies. PATIENTS AND METHODS: Treatment-naive advanced melanoma patients received nivolumab+ipilimumab or nivolumab monotherapy. To decrease immortal time bias, 3-, 6-, or 12-month overall survival (OS) and progression-free survival (PFS) landmark analyses were performed. Association between characteristics and response was evaluated by univariate and multivariate analyses. RESULTS: Response rates at any time were 58 % (239/409) for nivolumab+ipilimumab and 44 % (230/526) for nivolumab monotherapy. In 12-month landmark analyses, 5-year OS rates for responders versus non-responders were 82 % versus 40 % with nivolumab+ipilimumab (HR=0.23 [95 % CI, 0.15-0.35]) and 76 % versus 32 % with nivolumab monotherapy (HR=0.22 [95 % CI, 0.16-0.31]). PFS rates were 83 % versus 32 % and 69 % versus 46 %, respectively. Similar strong associations between response at 3 and 6 months and 5-year OS and PFS were also observed with more than 70 % of the responses observed in the first 3 months. Response rates correlated with baseline LDH and PD-L1 status by multivariate analysis but the association between response and long-term survival was maintained in landmark analyses even among patients with high LDH and low PD-L1 expression. CONCLUSION: Clinical response evaluated in the first months of therapy is a strong predictor of long-term survival, even in patients with poor prognostic biomarkers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 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".