Literature DB >> 33578627

Development and validation of a risk stratification nomogram for predicting prognosis in bone metastatic breast cancer: A population-based study.

Niuniu Hou1, Jun Yi1, Zhe Wang1, Lu Yang1, Ying Wu1, Meiling Huang1, Guangdong Hou2, Rui Ling1.   

Abstract

ABSTRACT: Bone metastasis seriously affects the survival of breast cancer. Therefore, the study aimed to explore the independent prognostic factors in bone metastatic breast cancer (BMBC) and to construct a prognostic nomogram that can accurately predict the survival of BMBC and strictly divide the patients into different risk stratification.Four thousand three hundred seventy six patients with BMBC from the surveillance, epidemiology, and end results database in 2010 to 2015 were collected and randomly divided into training and validation cohort. Multivariate Cox regression identified the independent prognostic factors of BMBC. A nomogram for predicting cancer-specific survival (CSS) in BMBC was created using R software. The predictive performance of the nomogram was evaluated by plotting receiver operating characteristic (ROC) curves and calibration curves.Marital status, race, age, T stage, tumor grade, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, brain metastasis, liver metastasis, lung metastasis, chemotherapy, and breast surgery were identified as independent prognostic factors for CSS of BMBC. The area under the ROC curve at 1-, 3-, and 5-year of the nomogram were 0.775, 0.756, and 0.717 in the internal validation and 0.785, 0.737, and 0.735 in the external validation, respectively. Calibration curves further confirmed the unbiased prediction of the model. Kaplan-Meier analysis verified the excellent risk stratification of our model.The first prognostic nomogram for BMBC constructed in our study can accurately predict the survival of BMBC, which may provide a practical tool to help clinicians evaluate prognosis and stratify the prognostic risk for BMBC, thereby determining which patients should be given intensive treatment and optimizing individual treatment strategies for BMBC.
Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.

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Year:  2021        PMID: 33578627     DOI: 10.1097/MD.0000000000024751

Source DB:  PubMed          Journal:  Medicine (Baltimore)        ISSN: 0025-7974            Impact factor:   1.889


  1 in total

1.  Clinical Features and Serological Markers Risk Model Predicts Overall Survival in Patients Undergoing Breast Cancer and Bone Metastasis Surgeries.

Authors:  Haochen Mou; Zhan Wang; Wenkan Zhang; Guoqi Li; Hao Zhou; Eloy Yinwang; Fangqian Wang; Hangxiang Sun; Yucheng Xue; Zenan Wang; Tao Chen; Xupeng Chai; Hao Qu; Peng Lin; Wangsiyuan Teng; Binghao Li; Zhaoming Ye
Journal:  Front Oncol       Date:  2021-09-17       Impact factor: 6.244

  1 in total

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