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Updated: Jul 20, 2025

Patient-derived Orthotopic Xenograft Models for Human Urothelial Cell Carcinoma and Colorectal Cancer Tumor Growth and Spontaneous Metastasis
Published on: May 12, 2019
A Survival Model for Patients with Upper Tract Urothelial Carcinoma
Chengliang Sun1, Xuewu Zhou2, Jiangyong Lou3
1Department of Urology, Wuchang Hospital Affiliated to Wuhan University of Science and Technology, 430063 Wuhan, Hubei, China.
Objectives:
We aimed to establish a survival model for patients with upper tract urothelial carcinoma (UTUC).
Methods:
A total of 241 patients with UTUC treated from January 2010 to December 2018 were selected. Their general clinical data were collected, and urological indices were measured. They were followed up after discharge, and divided into a death group (n = 51) and a survival group (n = 190) to compare the clinical data. Multivariate logistic regression analysis was performed to analyze the independent risk factors for postoperative death, based on which a nomogram prediction model was established and then validated.
Results:
The death group had significantly older age, larger tumor diameter, and higher tumor grade, pathological stage and proportion of no adjuvant chemotherapy than those of the control group (p < 0.01). The results of multivariate logistic analysis suggested that high tumor grade, tumor located in the ureter, large tumor diameter, high pathological stage, and lymph node metastasis were independent risk factors for postoperative death. A nomogram prediction model was established based on the prognostic independent risk factors. The area under the curve of receiver operating characteristic curve was 0.828 (95% confidence interval (CI): 0.801-0.845), so the model had good discrimination. The calibration curve showed that the model had high consistency.
Conclusions:
The established nomogram model can be used to predict the mortality risk of patients with UTUC and postoperative survival, and to develop individualized treatment plans for improving the prognosis and survival.
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