It is valuable to predict the time to the development of castration-resistant prostate cancer (CRPC) in patients with advanced prostate cancer (PCa). This study aimed to build and validate a nomogram incorporating the clinicopathologic characteristics and the parameters of contrast-enhanced ultrasonography (CEUS) to predict the time to CRPC after androgen deprivation therapy (ADT).
Patients with PCa were divided into the training (n = 183) and validation cohorts (n = 37) for nomogram construction and validation. The clinicopathologic characteristics and CEUS parameters were analyzed to determine the independent prognosis factors and serve as the basis of the nomogram to estimate the risk of 1-, 2-, and 3-year progress to CRPC.
T stage, distant metastasis, Gleason score, area under the curve (AUC), prostate-specific antigen (PSA) nadir, and time to PSA nadir were the independent predictors of CRPC (all P < 0.05). Three nomograms were built to predict the time to CRPC. Owing to the inclusion of CEUS parameter, the discrimination of the established nomogram (C-index: 0.825 and 0.797 for training and validation datasets) was improved compared with the traditional prediction model (C-index: 0.825 and 0.797), and when it excluded posttreatment PSA, it still obtained an acceptable discrimination (C-index: 0.825 and 0.797).
The established nomogram including regular prognostic indicators and CEUS obtained an improved accuracy for the prediction of the time to CRPC. It was also applicable for early prediction of CRPC when it excluded posttreatment PSA, which might be helpful for individualized diagnosis and treatment.
Clinical Medicine Insights. Oncology. 2021 Oct 08*** epublish ***
Yun-Xin Zhao, Guang-Li Yao, Jian Sun, Xiao-Lian Wang, Ying Wang, Qiu-Qiong Cai, Hui-Li Kang, Li-Ping Gu, Jia-Shun Yu, Wen-Min Li, Bei Zhang, Jian Wang, Jiang-Jun Mei, Yi Jiang
Department of Ultrasound, Shanghai Punan Hospital of Pudong New District, Shanghai, China., Department of Urology, Shanghai Punan Hospital of Pudong New District, Shanghai, China., Department of Ultrasound, Zhoupu Hospital, Shanghai Medical College, Shanghai, China.