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Cumulative receiver operating characteristics for analyzing interaction between tissue visfatin and clinicopathologic factors in breast cancer progression

Overview of attention for article published in Cancer Cell International, February 2018
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Title
Cumulative receiver operating characteristics for analyzing interaction between tissue visfatin and clinicopathologic factors in breast cancer progression
Published in
Cancer Cell International, February 2018
DOI 10.1186/s12935-018-0517-z
Pubmed ID
Authors

Sin-Hua Moi, Yi-Chen Lee, Li-Yeh Chuang, Shyng-Shiou F. Yuan, Fu Ou-Yang, Ming-Feng Hou, Cheng-Hong Yang, Hsueh-Wei Chang

Abstract

Visfatin has been reported to be associated with breast cancer progression, but the interaction between the visfatin and clinicopathologic factors in breast cancer progression status requires further investigation. To address this problem, it is better to simultaneously consider multiple factors in sensitivity and specificity assays. In this study, a dataset for 105 breast cancer patients (84 disease-free and 21 progressing) were chosen. Individual and cumulative receiver operating characteristics (ROC) were used to analyze the impact of each factor along with interaction effects. In individual ROC analysis, only 3 of 13 factors showed better performance for area under curve (AUC), i.e., AUC > 7 for hormone therapy (HT), tissue visfatin, and lymph node (LN) metastasis. Under our proposed scoring system, the cumulative ROC analysis provides higher AUC performance (0.746-0.886) than individual ROC analysis in predicting breast cancer progression. Considering the interaction between these factors, a minimum of six factors, including HT, tissue visfatin, LN metastasis, tumor stage, age, and tumor size, were identified as being highly interactive and associated with breast cancer progression, providing potential and optimal discriminators for predicting breast cancer progression. Taken together, the cumulative ROC analysis provides better prediction for breast cancer progression than individual ROC analysis.

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Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 21%
Student > Ph. D. Student 3 21%
Student > Bachelor 1 7%
Librarian 1 7%
Professor 1 7%
Other 0 0%
Unknown 5 36%
Readers by discipline Count As %
Medicine and Dentistry 3 21%
Biochemistry, Genetics and Molecular Biology 2 14%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Computer Science 1 7%
Business, Management and Accounting 1 7%
Other 2 14%
Unknown 4 29%