Literature DB >> 30022329

Population-based validation of the National Cancer Comprehensive Network recommendations for breast cancer staging.

Omar Abdel-Rahman1,2.   

Abstract

OBJECTIVE: The aim of the current study is to evaluate the performance characteristics of the National Comprehensive Cancer Network (NCCN) staging recommendations for breast cancer with regard to the detection of lung, bone, and liver metastases.
METHODS: Surveillance, epidemiology, and end points (SEER) database (2010-2015) was accessed, and patients with breast cancer and complete information about T stage and clinical N stage, ER status, Her2 status, and metastatic sites were extracted. Performance characteristics evaluated for the current study included sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), number needed to investigate (NNI), and accuracy.
RESULTS: A total of 239,196 patients were included in the analysis. For the overall cohort, the required PPV (for the recognition of lung metastases) is 10.6% and NNI to detect one case of lung metastasis is 9.4. Likewise, PPV (for the recognition of bone metastases) is 18.6% and NNI to detect one case of bone metastasis is 5.3. Moreover, PPV (for the recognition of liver metastases) is 7.6% and NNI to detect one case of liver metastasis is 13.1. When changing the threshold for baseline imaging to includeT2N1 patients, a better balance between sensitivity and specificity among ER+/Her2- patients (> 92% for both sensitivity and specificity for the three metastatic sites) was observed. On the other hand, the proposed change improved sensitivity while it lowers significantly the specificity among Her2+ and triple negative subtypes (specificity < 84% for Her2+ disease for the three metastatic sites; specificity < 87% for triple negative disease for the three metastatic sites).
CONCLUSION: The current NCCN recommendations for breast cancer staging have an excellent NPV and miss only few patients with lung, liver, or bone metastases. Future studies incorporating the subtype of breast cancer as a determinant of staging pathway is needed.

Entities:  

Keywords:  Breast cancer; NCCN; Prognosis; SEER; Staging

Mesh:

Substances:

Year:  2018        PMID: 30022329     DOI: 10.1007/s10549-018-4893-9

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  2 in total

1.  A gene expression signature-based nomogram model in prediction of breast cancer bone metastases.

Authors:  Chenglong Zhao; Yan Lou; Yao Wang; Dongsheng Wang; Liang Tang; Xin Gao; Kun Zhang; Wei Xu; Tielong Liu; Jianru Xiao
Journal:  Cancer Med       Date:  2018-12-21       Impact factor: 4.452

2.  Risk factors, prognostic factors, and nomograms for bone metastasis in patients with newly diagnosed infiltrating duct carcinoma of the breast: a population-based study.

Authors:  Zhangheng Huang; Chuan Hu; Kewen Liu; Luolin Yuan; Yinglun Li; Chengliang Zhao; Chanchan Hu
Journal:  BMC Cancer       Date:  2020-11-25       Impact factor: 4.430

  2 in total

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