RP1 Combined With Nivolumab in Advanced Anti–PD-1–Failed Melanoma (IGNYTE)
Bibliographic record
Abstract
PURPOSE Effective treatment options for melanoma after immune checkpoint blockade failure are limited. RP1 (vusolimogene oderparepvec) is a herpes simplex virus type 1–based oncolytic immunotherapy, here evaluated in combination with nivolumab in anti–PD-1–failed melanoma. METHODS Patients had advanced melanoma that had confirmed progression on anti–PD-1 (≥8 weeks, last prior treatment). RP1 was administered intratumorally (≤8 doses, ≤10 mL/dose; additional doses allowed) with nivolumab (≤2 years). The objective response rate (ORR) was assessed by independent central review using Response Evaluation Criteria in Solid Tumors version 1.1. RESULTS Of 140 patients enrolled, 48.6% had stage IVM1b/c/d disease, 65.7% had primary anti–PD-1 resistance, 56.4% were PD-L1 negative, and 46.4% received prior anti–PD-1 and anti–cytotoxic T-lymphocyte antigen-4 therapy (43.6% in combination and 2.9% sequentially). Confirmed ORR (95% CI) was 32.9% (95% CI, 25.2% to 41.3%; 15.0% complete response). Responses occurred with similar frequency, depth, duration, and kinetics for injected and noninjected, including visceral lesions. The median (95% CI) duration of response was 33.7 (95% CI, 14.1 to not reached) months. Overall survival rates (95% CI) at 1 and 2 years were 75.3% (95% CI, 66.9% to 81.9%) and 63.3% (95% CI, 53.6% to 71.5%), respectively. Biomarker analysis demonstrated broad immune activation associated with response, including increased CD8 + T-cell infiltration and PD-L1 expression. Treatment-related adverse event rates were 77.1% grade 1/2, 9.3% grade 3, 3.6% grade 4, and no grade 5 events. CONCLUSION RP1 combined with nivolumab provided deep and durable systemic responses in patients with anti–PD-1–failed melanoma, including those with poor prognostic factors. The safety profile was favorable, with mostly grade 1/2 adverse events.
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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 | 0.001 | 0.000 |
| 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".