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

BACKGROUND: 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...

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Detalles Bibliográficos
Autores principales: Moi, Sin-Hua, Lee, Yi-Chen, Chuang, Li-Yeh, Yuan, Shyng-Shiou F., Ou-Yang, Fu, Hou, Ming-Feng, Yang, Cheng-Hong, Chang, Hsueh-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807850/
https://www.ncbi.nlm.nih.gov/pubmed/29449787
http://dx.doi.org/10.1186/s12935-018-0517-z
Descripción
Sumario:BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Taken together, the cumulative ROC analysis provides better prediction for breast cancer progression than individual ROC analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-018-0517-z) contains supplementary material, which is available to authorized users.