Opinion - (2025) Volume 17, Issue 2
Received: 01-Mar-2025, Manuscript No. jcst-25-168223;
Editor assigned: 03-Mar-2025, Pre QC No. P-168223;
Reviewed: 15-Mar-2025, QC No. Q-168223;
Revised: 21-Mar-2025, Manuscript No. R-168223;
Published:
29-Mar-2025
, DOI: 10.37421/1948-5956.2025.17.695
Citation: Cabrera, Enrique. “Predicting Outcomes in Advanced Penile Squamous Cell Carcinoma.” J Cancer Sci Ther 17 (2025): 695.
Copyright: © 2025 Cabrera E. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
A major advancement in predicting outcomes in advanced penile SCC is the use of post-surgical loco-regional pathological staging to model cancer-specific mortality. Sun et al. (2015) developed a validated prognostic tool that incorporates multiple variables, such as nodal stage, extranodal extension and lymphovascular invasion. This model demonstrated a strong ability to predict cancer-specific survival, providing urologists and oncologists with a structured framework for patient counseling and treatment planning. Notably, the tool emphasized the significance of integrating comprehensive pathological data rather than relying solely on tumor size or depth of invasion. These tools are especially valuable in guiding the intensity of surveillance, adjuvant therapy decisions and consideration of pelvic lymphadenectomy in high-risk patients.
Complementing this, Velazquez et al. (2008) highlighted that histologic grade and perineural invasion are stronger predictors of nodal metastasis than tumor thickness in cases with 5-10 mm invasion. Their findings suggest that not all tumors with similar physical dimensions carry the same metastatic potential. This reinforces the importance of microscopic characteristics over macroscopic ones in determining prognosis. By identifying perineural invasion and poor differentiation as indicators of nodal spread, clinicians can more accurately stratify patients who may benefit from aggressive staging procedures or adjuvant treatments. Moreover, these insights shift the emphasis in pathology reporting and treatment algorithms toward biologically relevant features, moving beyond traditional TNM-based assessments [2].
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