Evidence map›Paper›PMID 33204161›Full record

ArticleCancer management and research2020

Prognostic Significance of a Novel Score Model Based on Preoperative Indicators in Patients with Breast Cancer Spine Metastases (BCSM).

Chenglong Zhao, Yao Wang, Xiaopan Cai, Wei Xu, Dongsheng Wang, Ting Wang, Qi Jia, Haiyi Gong, Haitao Sun, Zhipeng Wu and 1 more

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Article in Cancer management and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Chenglong Zhao *Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Yao Wang *Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Xiaopan Cai *Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Wei Xu *Spine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Dongsheng WangSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Ting WangSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Qi JiaSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Haiyi GongSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Haitao SunSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Zhipeng WuSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.
Jianru XiaoSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Navy Medical University, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurgery remains the mainstay of treatment for breast cancer spinal metastasis (BCSM) to relieve symptoms and improve the quality of life of BCSM patients. Therefore, it is important to effectively predict the prognosis of patients to determine whether they can undergo surgical operation. However, the prevalent methods for prognosis evaluation lack specificity and sensitivity for indicated malignancies like breast cancer because they are built on a relatively small number of heterogeneous types of primary tumors. The aim of the present study was to explore a novel predictive model based on the clinical, pathological and blood parameters obtained from BCSM patients before they received surgical intervention.

methodsAltogether, 144 patients were included in this study. Univariate and multivariate analyses were performed to investigate the significance of preoperative parameters and identify independent factors for prognostic prediction of BCSM. A nomogram for survival prediction was then established and validated. Time-dependent ROC (TDROC) curves were graphed to evaluate the accuracy of the novel model vs other scoring systems including Tomita Score, revised Tokuhashi Score, modified Bauer Score and New England Spinal Metastasis Score.

resultsIndependent factors, including preoperative postmenopausal (

conclusionWe constructed a nomogram model known as CZ Score based on the significant factors to predict the prognosis for BCSM patients. The result showed that CZ Score had a better value for prognostic evaluation and surgical decision-making as compared with the other scoring systems.

Indexed as

breast cancernomogramprognosisscoring systemspine metastases

Identifiers

PMID33204161
PMCPMC7667004

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