Establishment and assessment of a nomogram for predicting prognosis in bone-metastatic prostate cancer

Author:

Liu Wenfei12,Wang Zhiyong3,Wu Yanying4,Li Lingchao1

Affiliation:

1. Department of Pain, The Second Hospital of Dalian Medical University, Dalian, Liaoning, P.R. China

2. Department of Urology, Tongren Second People’s Hospital, Bijiang District, Tongren, Guizhou, P.R. China

3. Department of Rehabilitation, Pengze county People’s Hospital, Jiujiang, Jiangxi, P.R. China

4. Department of Oncology, Dalian Huayuankou Xincheng Hospital, Dalian, Liaoning, P.R. China.

Abstract

Objective: For the purposes of patients’ consultation, condition assessments, and guidance for clinicians’ choices, we developed a prognostic predictive model to evaluate the 1-, 3-, and 5-year overall survival (OS) rates of bone-metastatic prostate cancer (PCa) patients. Methods: We gathered data from 5522 patients with bone metastatic PCa registered in the Surveillance, Epidemiology, and End Results (SEER) database to develop a nomogram. A total of 359 bone metastatic PCas were collected from 2 hospitals to validate the nomogram and assess its discriminatory ability. In addition, we plotted the actual survival against the predicted risk to assess the calibration accuracy. Moreover, we designed a web calculator to quickly obtain accurate survival probability outcomes. Results: Univariate and multivariate Cox hazard regression analyses suggested that age, marital status, prostate-specific antigen (PSA) level, Gleason score, clinical T stage, N stage, surgery, and chemotherapy were closely associated with OS rates. The calibration charts of the training and validation groups showed a high accuracy and reliability. The decision curve analysis (DCA) suggested a favorable clinical net benefit. Conclusion: Based on demography and clinical pathology, we developed a reliable nomogram to help clinicians more accurately predict the 1-, 3-, and 5-year OS rates of patients with bone metastatic PCa to guide evaluation and treatment.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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