4.6 Article

Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer

期刊

FRONTIERS IN ONCOLOGY
卷 11, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2021.690324

关键词

bladder cancer; lymph node metastasis; prognosis; risk; nomogram

类别

资金

  1. Beijing Municipal Science and Technology Project [Z201100005620007]
  2. Beijing Hospital Clinical Research 121 Project [BJ-2018-090]
  3. Beijing Dongcheng District Outstanding Talent Funding Project [BJ-2020-047]

向作者/读者索取更多资源

This study identified clinicopathological factors associated with lymph node metastasis in bladder cancer and developed a nomogram for predicting prognosis. The nomogram showed high accuracy in predicting LNM, assisting in optimal treatment selection for patients.
Lymph node metastasis (LNM) is an important prognostic factor for bladder cancer (BCA) and determines the treatment strategy. This study aimed to determine related clinicopathological factors of LNM and analyze the prognosis of BCA. A total of 10,653 eligible patients with BCA were randomly divided into training or verification sets using the 2004-2015 data of the Surveillance, Epidemiology, and End Results database. To identify prognostic factors for the overall survival of BCA, we utilized the Cox proportional hazard model. Independent risk factors for LNM were evaluated via logistic regression analysis. T-stage, tumor grade, patient age and tumor size were identified as independent risk factors for LNM and were used to develop the LNM nomogram. The Kaplan-Meier method and competitive risk analyses were applied to establish the influence of lymph node status on BCA prognosis. The accuracy of LNM nomogram was evaluated in the training and verification sets. The areas under the receiver operating characteristic curve (AUC) showed an effective predictive accuracy of the nomogram in both the training (AUC: 0.690) and verification (AUC: 0.704) sets. In addition, the calibration curve indicated good consistency between the prediction of deviation correction and the ideal reference line. The decision curve analysis showed that the nomogram had a high clinical application value. In conclusion, our nomogram displayed high accuracy and reliability in predicting LNM. This could assist the selection of the optimal treatment for patients.

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