Related Experiment Video
Updated: Feb 11, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Primary urethral carcinoma: A Surveillance, Epidemiology, and End Results data analysis identifying predictors of
Ilija Aleksic1, Soroush Rais-Bahrami2,3, Michael Daugherty4
1Division of Urology, Albany Medical Center, Albany, NY, USA.
Objectives:
Primary urethral carcinoma (PUC) is rare, accounting for <1% of genitourinary malignancies. Current knowledge regarding is founded upon tertiary care centers reporting their experiences. We aim to identify factors predictive of outcomes using a nationwide registry database.
Materials And Methods:
The Surveillance, Epidemiology, and End Results-18 registries database was queried for cases of PUC ranging between 2004 and 2010. To identify PUC cases, ICD-O site code C68.0 was used as a filter, hence identifying PUC with histologic subtypes including urothelial carcinoma (UC), squamous cell carcinoma (SCC), and adenocarcinoma (AC). Tumor characteristics were compared using log-rank analysis, and survival outcomes were compared using Cox proportional hazards models.
Results:
A total of 419 PUC cases were identified, 250 (59.7%) male and 169 (40.3%) female patients. The most common histology in men was UC (134, 53.6%), followed by SCC (87, 34.8%) and AC (29, 11.6%). The most common histology in women was AC (79, 46.7%), followed by SCC (43, 25.4%) and UC (42, 24.9%). Log-rank analysis illustrated significant difference in cancer-specific survival (CSS) for T-stage, N-stage, M-stage, and stage of PUC with all histological variants combined (P < 0.001). Multivariate Cox proportional hazards model demonstrated that stage and age were significant for survival, with a risk ratio of 1.033 (95% confidence interval [CI], 1.020-1.046)/year of increased age (P < 0.001) and 3.71 (95% CI, 2.72-5.05) for patients with regional or distant spread.
Conclusions:
Knowledge of patient and tumor characteristics that influences survival is paramount in dictating management. The present study illustrates that age and stage are factors significantly associated with CSS in PUC.
Related Concept Videos
Cancer Survival Analysis
Censoring Survival Data
Statistical Methods for Analyzing Epidemiological Data
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Comparing the Survival Analysis of Two or More Groups
Truncation in Survival Analysis
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...

