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Updated: Jul 20, 2025
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and validation of a predictive model for penile cancer based on the surveillance, epidemiology, and end
Shujun Yang1, Wei Chang1, Bin Zhang1
1Department of Urology, Lanzhou University Second Hospital, Chengguan District, Lanzhou, 730030, Gansu, China.
Purpose:
Penile cancer (PC) is a great impact on the quality of life and psychological status of patients. This study aimed to construct nomograms using data from the Surveillance, Epidemiology, and End Results (SEER) database to predict overall survival (OS) and cancer-specific survival (CSS) in patients with penile cancer (PC).
Methods:
Patients were divided into a training cohort (n = 634) and a validation cohort (n = 272) in a 7:3 ratio. Independent risk factors influencing the prognosis of PC were screened using univariate and multivariate Cox analyses, and models for predicting PC were developed. Data from 203 patients with PC in four tertiary hospitals in Gansu Province from 2012 to 2021 were externally validated.
Results:
Univariate analysis and multivariate analysis showed revealed that the OS-related factors were age, grade, T stage, N stage, M stage and tumor size (p < 0.05); the CSS-related factors were age, mode of surgery, T stage, N stage, M stage and tumor size (p < 0.05). The C-indices of the OS and CSS nomograms in the training cohort were 0.743 [95% confidence interval (CI) (0.714-0.772)] and 0.797 (0.762-0.832), respectively. The C-indices of the OS and CSS nomograms in the internal validation cohort were 0.735 (0.686-0.784) and 0.755 (0.688-0.822), respectively, and those in the external validation cohort were 0.801 (0.746-0.856) and 0.863 (0.812-0.914), respectively. Receiver operating characteristic (ROC) curves, calibration curves, and survival curves all demonstrated good predictive performance of the nomograms.
Conclusion:
The nomograms for PC were developed using the SEER database. The accuracy and clinical usefulness of the model were validated through a combination of internal and external validations.
