title: Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer.
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< 0.001).
  
  
  CONCLUSIONS
  Patients with MBC have a better prognosis than patients with IDC. Nomograms could help clinicians make more informed decisions in clinical practice. The competing risk regression model, as a more rational model, is recommended for use in the survival analysis of patients with MBC in the future.
authors.affiliation: Department of Oncology, Zhejiang University Jinhua hospital, Jinhua, Zhejiang Province, China.
authors.forename: Jianfei
authors.initials: J
authors.lastname: Fu
authors.affiliation: Department of Gastroenterology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.|Institute of Gastroenterology, Zhejiang University, Hangzhou, Zhejiang Province, China.
authors.forename: Lunpo
authors.initials: L
authors.lastname: Wu
authors.affiliation: Department of Radiation Oncology, The First Affiliated Hospital of ZheJiang Chinese Medical University, Zhejiang Provincial Hospital of TCM, Hangzhou, Zhejiang Province, China.
authors.forename: Mengjie
authors.initials: M
authors.lastname: Jiang
authors.affiliation: Department of Medical Oncology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.|Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, Chinese National Ministry of Education; Key Laboratory of Molecular Biology in Medical Sciences, Zhejiang Province, China), Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
authors.forename: Dan
authors.initials: D
authors.lastname: Li
authors.affiliation: Department of Nuclear Medicine, Zhejiang University Jinhua hospital, Jinhua, Zhejiang Province, China.
authors.forename: Ting
authors.initials: T
authors.lastname: Jiang
authors.affiliation: Department of Oncology, Zhejiang University Jinhua hospital, Jinhua, Zhejiang Province, China.
authors.forename: Zhongwu
authors.initials: Z
authors.lastname: Hong
authors.affiliation: Department of Oncology, Zhejiang University Jinhua hospital, Jinhua, Zhejiang Province, China.
authors.forename: Fan
authors.initials: F
authors.lastname: Wang
authors.affiliation: Department of Oncology, Zhejiang University Jinhua hospital, Jinhua, Zhejiang Province, China.
authors.forename: Shuguang
authors.initials: S
authors.lastname: Li
mesh_terms: D002288:Adenocarcinoma, Mucinous / Q000453:epidemiology* / Q000378:metabolism / Q000401:mortality; D000368:Aged; D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000453:epidemiology* / Q000378:metabolism / Q000401:mortality; D018270:Carcinoma, Ductal, Breast / Q000453:epidemiology* / Q000378:metabolism / Q000401:mortality; D005260:Female; D006801:Humans; D008207:Lymphatic Metastasis; D008875:Middle Aged; D060787:Neoplasm Grading; D011379:Prognosis; D011960:Receptors, Estrogen / Q000378:metabolism*; D012307:Risk Factors; D018426:SEER Program; D016019:Survival Analysis
chemical_list: D011960:Receptors, Estrogen