Asset Details
Do you wish to reserve the book?
Competing‐risks model for predicting the prognosis of penile cancer based on the SEER database
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Competing‐risks model for predicting the prognosis of penile cancer based on the SEER database
Do you wish to request the book?
Competing‐risks model for predicting the prognosis of penile cancer based on the SEER database
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Competing‐risks model for predicting the prognosis of penile cancer based on the SEER database
2019
Overview
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. 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.
