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. 2023 Nov;149(15):13665-13676.
doi: 10.1007/s00432-023-04784-1. Epub 2023 Jul 31.

Development and validation of a predictive model for penile cancer based on the surveillance, epidemiology, and end results database and multi-center cases

Shujun Yang #  1 , Wei Chang #  1 , Bin Zhang  1 , Qian Hou  1 , Biao Zhang  1 , Yindong Kang  2 , Yongsheng Yin  3 , Jianghou Wan  4 , Panfeng Shang  5
Affiliations

Development and validation of a predictive model for penile cancer based on the surveillance, epidemiology, and end results database and multi-center cases

Shujun Yang et al. J Cancer Res Clin Oncol. 2023 Nov.

Abstract

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.

Keywords: Cancer specific survival; Nomogram; Overall survival; Penile cancer.

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Conflict of interest statement

The authors declared no conflict of interest.

Figures

Fig. 1
Fig. 1
Flowchart for screening patients for the SEER database PC and for the external validation of clinical data
Fig. 2
Fig. 2
Nomograms of PC patients (1-, 3-,5- and 8-year): a OS; b CSS
Fig. 3
Fig. 3
Area under the ROC curve (AUC value) used to measure the performance of the OS and CSS nomogram. 5-year ROC curves for OS and CSS in the training cohort (a, d); 5-year ROC curves for OS and CSS in the internal validation cohort (b, e); 5-year ROC curves for OS and CSS in the external validation cohort (c, f)
Fig. 4
Fig. 4
Nomogram calibration curves for OS and CSS 5-year calibration curves for OS and CSS in the training cohort (a, d); 5-year calibration curves for OS and CSS in the internal validation cohort; 5-year calibration curves for OS and CSS in the external validation cohort
Fig. 5
Fig. 5
Survival curves for the internal (a, b) and external (c, d) validation cohorts by high and low scores
See this image and copyright information in PMC

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