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Survival nomogram for patients with bone metastatic renal cell carcinoma: A population-based study
Wang, Keyi; Wu, Zonglin; Wang, Guangchun; Shi, Heng; Xie, Jinbo; Yin, Lei; Xu, Tianyuan; Mao, Weipu; Peng, Bo.
  • Wang, Keyi; Tongji University. School of Medicine. Peoples Hospital of Putuo District. Shanghai. CN
  • Wu, Zonglin; Tongji University. School of Medicine. Peoples Hospital of Putuo District. Shanghai. CN
  • Wang, Guangchun; Tongji University. School of Medicine. Shanghai Tenth Peoples Hospital. Shanghai. CN
  • Shi, Heng; Tongji University. School of Medicine. Shanghai Tenth Peoples Hospital. Shanghai. CN
  • Xie, Jinbo; Tongji University. School of Medicine. Shanghai Tenth Peoples Hospital. Shanghai. CN
  • Yin, Lei; Tongji University. School of Medicine. Shanghai Tenth Peoples Hospital. Shanghai. CN
  • Xu, Tianyuan; Tongji University. School of Medicine. Shanghai Tenth Peoples Hospital. Shanghai. CN
  • Mao, Weipu; Southeast University. Affiliated Zhongda Hospital. Department of Urology. Nanjing. CN
  • Peng, Bo; Tongji University. School of Medicine. Peoples Hospital of Putuo District. Shanghai. CN
Int. braz. j. urol ; 47(2): 333-349, Mar.-Apr. 2021. tab, graf
Article in English | LILACS | ID: biblio-1154476
ABSTRACT
ABSTRACT

Purpose:

Increased attention has been focused on the survival of renal cell carcinoma (RCC) patients with bone metastasis. This study proposed to establish and evaluate a nomogram for predicting the overall survival (OS) and cancer-specific survival (CSS) of RCC patients with bone metastasis. Materials and

Methods:

RCC patients with bone metastasis between 2010 and 2015 were captured from the surveillance, epidemiology and end results (SEER) database. Univariate and multivariate cox regressions were performed to assess the effects of clinical variables on OS and CSS. The nomogram based on the Cox hazards regression model was developed. Concordance index (C-index) and calibration curve were performed to evaluate the accuracy of nomogram models, receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were conducted to assess the predict performance.

Results:

A total of 2.471 eligible patients were enrolled in this study. The patients were assigned to primary (n=1.672) and validation (n=799) cohorts randomly. The 1-, 2-, and 3-year OS and CSS nomogram models were constructed based on age at diagnosis, sex, marital status, pathological grade, T-stage, N-stage, brain/liver/lung metastasis, surgery, radiotherapy and chemotherapy. The c for OS and CSS prediction was 0.730 (95% confidence interval [CI] 0.719-0.741) and 0.714 (95%CI0.702-0.726). The calibration curves showed significant agreement between nomogram models and actual observations. ROC and DCA indicated nomograms had better predict performance.

Conclusions:

The nomograms for predicting prognosis provided an accurate prediction of OS and CSS in RCC patients with bone metastasis, and contributed clinicians to optimize individualized treatment plans.
Subject(s)


Full text: Available Index: LILACS (Americas) Main subject: Carcinoma, Renal Cell / Neoplasm Staging Type of study: Controlled clinical trial / Prognostic study Limits: Humans Language: English Journal: Int. braz. j. urol Journal subject: Urology Year: 2021 Type: Article Affiliation country: China Institution/Affiliation country: Southeast University/CN / Tongji University/CN

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Full text: Available Index: LILACS (Americas) Main subject: Carcinoma, Renal Cell / Neoplasm Staging Type of study: Controlled clinical trial / Prognostic study Limits: Humans Language: English Journal: Int. braz. j. urol Journal subject: Urology Year: 2021 Type: Article Affiliation country: China Institution/Affiliation country: Southeast University/CN / Tongji University/CN