Competing‐risks model for predicting the prognosis of penile cancer based on the SEER database

OBJECTIVES: This study performed a competing‐risks analysis using data from the SEER database on penile cancer patients with the aim of identifying more accurate prognostic factors. METHODS: Data on patients with penile cancer were extracted from the SEER database. A univariate analysis used the cumulative incidence function and Gray's test, while multivariate analysis was performed using the Fine‐Gray model. Cumulative hazards were compared with a competing‐risks model constructed using Kaplan‐Meier estimation. RESULTS: The multivariate Fine‐Gray analysis indicated that being black (HR = 1.51, 95%CI: 1.10‐2.07, P = .01), AJCC stage II (HR = 1.94, 95%CI: 1.36‐2.77, P < .001), AJCC stage III (HR = 1.98, 95%CI: 1.34‐2.91, P < .001), tumor size > 5 cm (HR = 2.23, 95%CI: 1.33‐3.72, P < .05), and TNM stages N1 (HR = 2.49, 95%CI: 1.71‐3.61, P < .001), N2 (HR = 3.25, 95%CI: 2.18‐4.84, P < .001), N3 (HR = 5.05, 95%CI: 2.69‐9.50, P < .001), and M1 (HR = 2.21, 95%CI: 1.28‐3.84, P < .05) were statistically significant. The results obtained using multivariate Cox regression were different, while Kaplan‐Meier curve analysis led to an overestimation of the cumulative risk of the patient. CONCLUSIONS: This study established a competing‐risks analysis model for the first time based on the SEER database for the risk assessment of penile cancer patients. The results may help clinicians to better understand penile cancer and provide these patients with more appropriate support.