A Novel Nomogram for Prediction and Evaluation of Lymphatic Metastasis in Patients With Renal Cell Carcinoma

Wenle Li; Bing Wang; Shengtao Dong; Chan Xu; Yang Song; Ximin Qiao; Xiaofeng Xu; Meijin Huang; Chengliang Yin

doi:10.3389/fonc.2022.851552

A Novel Nomogram for Prediction and Evaluation of Lymphatic Metastasis in Patients With Renal Cell Carcinoma

Front Oncol. 2022 Apr 11:12:851552. doi: 10.3389/fonc.2022.851552. eCollection 2022.

Authors

Wenle Li¹, Bing Wang¹, Shengtao Dong², Chan Xu¹, Yang Song³, Ximin Qiao^{1

4}, Xiaofeng Xu^{1

4}, Meijin Huang⁵, Chengliang Yin⁶

Affiliations

¹ Clinical Medical Research Center, Xianyang Central Hospital, Xianyang, China.
² Department of Spine Surgery, Second Affifiliated Hospital of Dalian Medical University, Dalian, China.
³ Department of Gastroenterology and Hepatology, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
⁴ Department of Urology, Xianyang Central Hospital, Xianyang, China.
⁵ Department of Oncology, 920th Hospital of People's Liberation Army (PLA) Joint Logistics Support Force, Yunnan, China.
⁶ Faculty of Medicine, Macau University of Science and Technology, Macau, Macau SAR, China.

Abstract

Background: Lymphatic metastasis is an important mechanism of renal cell carcinoma (RCC) dissemination and is an indicator of poor prognosis. Therefore, we aimed to identify predictors of lymphatic metastases (LMs) in RCC patients and to develop a new nomogram to assess the risk of LMs.

Methods: This study included patients with RCC from 2010 to 2018 in the Surveillance, Epidemiology, and Final Results (SEER) database into the training cohort and included the RCC patients diagnosed during the same period in the Second Affiliated Hospital of Dalian Medical University into the validation cohort. Univariate and multivariate logistic regression analysis were performed to identify risk factors for LM, constructing a nomogram. The receiver operating characteristic (ROC) curves were generated to assess the nomogram's performance, and the concordance index (C-index), area under curve value (AUC), and calibration plots were used to evaluate the discrimination and calibration of the nomogram. The nomogram's clinical performance was evaluated by decision curve analysis (DCA), probability density function (PDF) and clinical utility curve (CUC). Furthermore, Kaplan-Meier curves were performed in the training and the validation cohort to evaluate the survival risk of the patients with lymphatic metastasis or not. Additionally, on the basis of the constructed nomogram, we obtained a convenient and intuitive network calculator.

Results: A total of 41837 patients were included for analysis, including 41,018 in the training group and 819 in the validation group. Eleven risk factors were considered as predictor variables in the nomogram. The nomogram displayed excellent discrimination power, with AUC both reached 0.916 in the training group (95% confidence interval (CI) 0.913 to 0.918) and the validation group (95% CI 0.895 to 0.934). The calibration curves presented that the nomogram-based prediction had good consistency with practical application. Moreover, Kaplan-Meier curves analysis showed that RCC patients with LMs had worse survival outcomes compared with patients without LMs.

Conclusions: The nomogram and web calculator (https://liwenle0910.shinyapps.io/DynNomapp/) may be a useful tool to quantify the risk of LMs in patients with RCC, which may provide guidance for clinicians, such as identifying high-risk patients, performing surgery, and establishing personalized treatment as soon as possible.

Keywords: lymphatic metastasis; multicenter; nomogram; renal cell carcinoma (RCC); web calculator.