Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer
Jianfei Fu,
Lunpo Wu,
Mengjie Jiang,
Dan Li,
Ting Jiang,
Zhongwu Hong,
Fan Wang and
Shuguang Li
PLOS ONE, 2016, vol. 11, issue 10, 1-16
Abstract:
Background: The features related to the prognosis of patients with mucinous breast cancer (MBC) remain controversial. We aimed to explore the prognostic factors of MBC and develop a nomogram for predicting survival outcomes. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was searched to identify 139611 women with resectable breast cancer from 1990 to 2007. Survival curves were generated using Kaplan-Meier methods. The 5-year and 10-year cancer-specific survival (CSS) rates were calculated using the Life-Table method. Based on Cox models, a nomogram was constructed to predict the probabilities of CSS for an individual patient. The competing risk regression model was used to analyse the specific survival of patients with MBC. Results: There were 136569 (97.82%) infiltrative ductal cancer (IDC) patients and 3042 (2.18%) MBC patients. Patients with MBC had less lymph node involvement, a higher frequency of well-differentiated lesions, and more estrogen receptor (ER)-positive tumors. Patients with MBC had significantly higher 5 and10-year CSS rates (98.23 and 96.03%, respectively) than patients with IDC (91.44 and 85.48%, respectively). Univariate and multivariate analyses showed that MBC was an independent factor for better prognosis. As for patients with MBC, the event of death caused by another disease exceeded the event of death caused by breast cancer. A competing risk regression model further showed that lymph node involvement, poorly differentiated grade and advanced T-classification were independent factors of poor prognosis in patients with MBC. The Nomogram can accurately predict CSS with a high C-index (0.816). Risk scores developed from the nomogram can more accurately predict the prognosis of patients with MBC (C-index = 0.789) than the traditional TNM system (C-index = 0.704, P
Date: 2016
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164921 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 64921&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0164921
DOI: 10.1371/journal.pone.0164921
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().