J Cancer 2021; 12(3):790-798. doi:10.7150/jca.50419
A Novel Nomogram for Predicting the Survival of Patients with Invasive Upper Tract Urothelial Carcinoma
1. Department of Urology, Shenzhen People's Hospital, The Second Clinic Medical College of Jinan University 518060, Shenzhen, Guangdong, P. R. China.
2. Department of Urology, First Affiliated Hospital of Southern University of Science and Technology, 518060, Shenzhen, Guangdong, P. R. China.
3. Department of Urology, Shenzhen Engineering and Technology Center of minimally Invasive Urology, Shenzhen People's Hospital, 518060, Shenzhen, Guangdong, P. R. China.
4. Department of Oncology, The Seventh Affiliated Hospital Sun Yat-sen University, 518107, Shenzhen, Guangdong, P. R. China.
5. Department of Urology, Sun Yat-sen University Cancer Center, 510060, Guangzhou, Guangdong, P. R. China.
6. State Key Laboratory of Oncology in South China, 510060, Guangzhou, Guangdong, P. R. China.
7. Collaborative Innovation Center of Cancer Medicine, 510060, Guangzhou, Guangdong, P. R. China.
8. Gynecology Department, Long-gang District Maternal and Child Healthcare Hospital, 518172, Shenzhen, Guangdong, P. R. China.
#These authors contributed equally to this research.
Li Z, Li X, Li Y, Liu Y, Du P, Liu Z, Xiao K. A Novel Nomogram for Predicting the Survival of Patients with Invasive Upper Tract Urothelial Carcinoma. J Cancer 2021; 12(3):790-798. doi:10.7150/jca.50419. Available from https://www.jcancer.org/v12p0790.htm
Purpose: Available tools for the prediction of the prognosis of patients with upper tract urothelial carcinoma (UTUC) are unified. We determined whether a novel nomogram is effective in estimating the survival of patients with invasive UTUC.
Methods: From January 2004 to December 2015, 4796 invasive UTUC patients in the Surveillance, Epidemiology and End Results database underwent radical nephroureterectomy (RNU) for invasive UTUC. The medical records of the patients were randomly (7:3) divided into the training and validation cohorts. The independent factors included in the nomogram were selected by multivariate analyses. The nomogram was developed based on the training cohort. Bootstrap validation was applied to validate the nomogram, whereas external validation was performed using the validation cohort. The accuracy and discrimination of the nomogram were assessed using concordance indices (C-indices) and calibration curves.
Results: The multivariate Cox regression model identified that age, tumor stage, node stage, metastasis stage and grade were associated with survival. In the training set, the nomogram, which included the above factors, exhibited discrimination power superior to that of the 8th American Joint Committee on Cancer (AJCC) TNM classification (Harrell's C-index, 0.74 vs. 0.71; P < 0.001). The nomogram showed better probability of survival agreement with the C-index than the AJCC-TNM staging system in the bootstrap validation (0.74 vs. 0.70; P < 0.001) and validation set (Harrell's C-index, 0.77 vs. 0.73; P < 0.001). The validation revealed that this nomogram exhibited excellent discrimination and calibration capacities.
Conclusion: An accurate novel nomogram that is superior to the current AJCC-TNM staging system was established for the prediction of CSS after RNU for invasive UTUC.
Keywords: urothelial carcinoma, upper urinary tract, prognosis, radical nephroureterectomy, mortality