Therapeutic Approaches to Penile Cancer: Standards of Care and Recent Developments
Bibliographic record
Abstract
Joshua White,1 Ross Mason,2 Tarek Lawen,2 Jesse Spooner,2 Kauy VM Faria,3 Farah Rahman,1 Ranjith Ramasamy1 1Department of Urology, University of Miami Miller School of Medicine, Miami, FL, USA; 2Department of Urology, Dalhousie University, Halifax, NS, Canada; 3Department of Urology, Institute of Cancer of São Paulo, University of São Paulo School of Medicine, Sao Paulo, BrazilCorrespondence: Ranjith Ramasamy, University of Miami, Miller School of Medicine, 1120 NW 14th Street, 15th Floor, Miami, FL, 33136, USA, Tel +1 201 388-6644, Email ramasamy@miami.eduAbstract: Penile cancer is a rare malignancy, most commonly diagnosed in older men, associated with poor outcomes, dramatic decline in quality of life and sexual function. Squamous cell carcinoma is the most common histopathology of penile cancer, accounting for 95% of all cases. Localized, early-stage penile cancer can be effectively managed through penile-sparing techniques in many cases, though advanced stages of penile cancer carry a poor prognosis. Current innovative treatments are exploring the role of targeted therapy, HPV-directed therapy, immune checkpoint inhibitors and adoptive T-cell therapies in treatment and prevention of relapse of penile cancer. Clinical trials are investigating the potential of targeted therapies and immune checkpoint inhibitors in advanced penile cancer. This review examines the current management of penile cancer and highlights future directions in research and treatment.Keywords: penile cancer, inguinal lymph node dissection, immunotherapy, targeted therapy, HPV, adoptive T-cell therapy, sexual function
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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 | 0.038 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".