Safety and efficacy of immune checkpoint inhibitors in advanced penile cancer: report from the Global Society of Rare Genitourinary Tumors
Bibliographic record
Abstract
BACKGROUND: Treatment options for penile squamous cell carcinoma are limited. We sought to investigate clinical outcomes and safety profiles of patients with penile squamous cell carcinoma receiving immune checkpoint inhibitors. METHODS: This retrospective study included patients with locally advanced or metastatic penile squamous cell carcinoma receiving immune checkpoint inhibitors between 2015 and 2022 across 24 centers in the United States, Europe, and Asia. Overall survival and progression-free survival were estimated using the Kaplan-Meier method. Objective response rates were determined per Response Evaluation Criteria in Solid Tumours 1.1 criteria. Treatment-related adverse events were graded per the Common Terminology Criteria for Adverse Events, version 5.0. Two-sided statistical tests were used for comparisons. RESULTS: Among 92 patients, 8 (8.7%) were Asian, 6 (6.5%) were Black, and 24 (29%) were Hispanic and/or Latinx. Median (interquartile range) age was 62 (53-70) years. In all, 83 (90%) had metastatic penile squamous cell carcinoma, and 74 (80%) had received at least second-line treatment. Most patients received pembrolizumab monotherapy (n = 26 [28%]), combination nivolumab-ipilimumab with or without multitargeted tyrosine kinase inhibitors (n = 23 [25%]), or nivolumab (n = 16 [17%]) or cemiplimab (n = 15 [16%]) monotherapies. Median overall and progression-free survival were 9.8 months (95% confidence interval = 7.7 to 12.8 months) and 3.2 months (95% confidence interval = 2.5 to 4.2 months), respectively. The objective response rate was 13% (n = 11/85) in the overall cohort and 35% (n = 7/20) in patients with lymph node-only metastases. Visceral metastases, Eastern Cooperative Oncology Group (ECOG) performance status of 1 or higher, and a higher neutrophil/lymphocyte ratio were associated with worse overall survival. Treatment-related adverse events occurred in 27 (29%) patients, and 9.8% (n = 9) of the events were grade 3 or higher. CONCLUSIONS: Immune checkpoint inhibitors are active in a subset of patients with penile squamous cell carcinoma. Future translational studies are warranted to identify patients more likely to derive clinical benefit from immune checkpoint inhibitors.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".