Biologic subtypes of melanoma predict survival benefit of combination anti-PD1+anti-CTLA4 immune checkpoint inhibitors versus anti-PD1 monotherapy
Bibliographic record
Abstract
Purpose Anti-programmed cell death protein 1 (PD1)±anti-cytotoxic T-lymphocyte associated protein 4 (CTLA4) immune checkpoint inhibitors (ICIs) are standard therapeutic options for metastatic melanoma. We assessed whether biologic subtype according to primary tumor type or genomic subtype can function as predictive biomarkers for anti-PD1±anti-CTLA4 ICI in patients with advanced melanoma. Methods We performed a single-center retrospective cohort analysis of patients who received anti-PD1±anti-CTLA4 ICI for advanced melanoma between 2012 and 2019. Primary tumor type, BRAF and NRAS mutation status, and other covariates were abstracted from chart review. Log-rank tests and multivariable Cox regression models were used to assess differences in clinical progression-free (cPFS) and overall survival (OS). Results We identified 230 patients who received 249 lines of anti-PD1±anti-CTLA4 ICI for unresectable or metastatic disease. Of these patients, 74% were cutaneous, 11% mucosal, 8% unknown primary and 7% acral. BRAF and NRAS mutations were identified in 35% and 28% of patients, respectively. In multivariable analyses of the entire cohort, acral or mucosal primary tumor type, >3 metastatic sites, elevated LDH were predictive of shorter cPFS and OS. Combination ICI therapy was associated with longer cPFS (HR 0.57, 95% CI 0.38 to 0.86, p=0.007) and OS (HR 0.42, 95% CI 0.28 to 0.65, p<0.001). Combination ICI was significantly associated with longer OS in unknown primary and mucosal melanoma. There was a non-significant trend toward longer OS with anti-PD1+anti-CTLA4 in cutaneous melanoma, but not in acral melanoma. In multivariable analyses, combination ICI was associated with longer OS in NRAS (HR 0.24, 95% CI 0.10 to 0.62, p=0.003, n=69) and BRAF V600E/K (HR 0.47, 95% CI 0.24 to 0.90, p=0.024, n=86) mutant melanoma but not BRAF/NRAS wild-type (n=94) melanoma. Conclusions In our cohort, primary melanoma tumor type and genomic subtype were independent predictive markers of cPFS and OS for patients with metastatic melanoma receiving anti-PD1 ICI. Primary tumor type and genomic subtype—including NRAS—should be further evaluated in prospective clinical trials to determine their value as predictive markers. Biologic subtypes may facilitate clinical decision-making when recommending combination ICI treatment (anti-PD1±anti-CTLA4) versus anti-PD1 alone for patients with metastatic melanoma.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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".