Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer

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.

[1]  Yanqi Huang,et al.  Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[2]  M. Reinfuss,et al.  Pure and Mixed Mucinous Carcinoma of the Breast: A Comparison of Clinical Outcomes and Treatment Results , 2016, The breast journal.

[3]  J. Vandenbroucke,et al.  Performing Survival Analyses in the Presence of Competing Risks: A Clinical Example in Older Breast Cancer Patients. , 2016, Journal of the National Cancer Institute.

[4]  Virginia G Kaklamani,et al.  Prospective Validation of a 21-Gene Expression Assay in Breast Cancer. , 2015, The New England journal of medicine.

[5]  Zhenhua Li,et al.  Invasive micropapillary mucinous carcinoma of the breast is associated with poor prognosis , 2015, Breast Cancer Research and Treatment.

[6]  Li Zhang,et al.  Development and validation of a nomogram for predicting survival in patients with resected non-small-cell lung cancer. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[7]  Steven Woloshin,et al.  Providing clinicians and patients with actual prognosis: cancer in the context of competing causes of death. , 2014, Journal of the National Cancer Institute. Monographs.

[8]  Kui Wang,et al.  Prognostic nomogram for intrahepatic cholangiocarcinoma after partial hepatectomy. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[9]  Paul C Lambert,et al.  Flexible parametric modelling of cause-specific hazards to estimate cumulative incidence functions , 2013, BMC Medical Research Methodology.

[10]  Jiong Wu,et al.  Outcome of Pure Mucinous Breast Carcinoma Compared to Infiltrating Ductal Carcinoma: A Population-based Study from China , 2012, Annals of Surgical Oncology.

[11]  Magali Lacroix-Triki,et al.  Mucinous carcinoma of the breast is genomically distinct from invasive ductal carcinomas of no special type , 2010, The Journal of pathology.

[12]  A. Ranade,et al.  Clinicopathological evaluation of 100 cases of mucinous carcinoma of breast with emphasis on axillary staging and special reference to a micropapillary pattern , 2010, Journal of Clinical Pathology.

[13]  Felipe C Geyer,et al.  Mucinous and neuroendocrine breast carcinomas are transcriptionally distinct from invasive ductal carcinomas of no special type , 2009, Modern Pathology.

[14]  S. di Saverio,et al.  A retrospective review with long term follow up of 11,400 cases of pure mucinous breast carcinoma , 2008, Breast Cancer Research and Treatment.

[15]  G. Raj,et al.  How to build and interpret a nomogram for cancer prognosis. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[16]  L. Kiemeney,et al.  Uncommon breast tumors in perspective: Incidence, treatment and survival in the Netherlands , 2007, International journal of cancer.

[17]  M. Cronin,et al.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.

[18]  D. Rimm,et al.  X-Tile , 2004, Clinical Cancer Research.

[19]  A. Troxel,et al.  Pure mucinous carcinoma of the breast. , 2004, American journal of surgery.

[20]  Yudong D. He,et al.  A Gene-Expression Signature as a Predictor of Survival in Breast Cancer , 2002 .

[21]  E. Gabrielson,et al.  Mucinous Cancers have Fewer Genomic Alterations than More Common Classes of Breast Cancer , 2002, Breast Cancer Research and Treatment.

[22]  J. Paramo,et al.  Pure mucinous carcinoma of the breast: Is axillary staging necessary? , 2002, Annals of Surgical Oncology.

[23]  G M Clark,et al.  Tumor characteristics and clinical outcome of tubular and mucinous breast carcinomas. , 1999, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[24]  I. Fentiman,et al.  Mucoid breast carcinomas: histology and prognosis. , 1997, British Journal of Cancer.

[25]  D. Wartenberg,et al.  The importance of histologic type on breast cancer survival. , 1997, Journal of clinical epidemiology.

[26]  J. Soares,et al.  Mucinous carcinoma of the breast: A pathologic study of 82 cases , 1995, Journal of surgical oncology.

[27]  A. Testori,et al.  Mucinous carcinoma of the breast. A clinicopathologic, histochemical, and immunocytochemical study with special reference to neuroendocrine differentiation. , 1994, The American journal of surgical pathology.

[28]  Y. Monden,et al.  Mucinous carcinoma of the breast in Japan. A prognostic analysis based on morphologic features , 1988, Cancer.

[29]  B. B. Rasmussen Human mucinous breast carcinomas and their lymph node metastases. A histological review of 247 cases. , 1985, Pathology, research and practice.

[30]  J. Reis-Filho,et al.  Absence of microsatellite instability in mucinous carcinomas of the breast. , 2010, International journal of clinical and experimental pathology.

[31]  T. Eberlein A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer , 2006 .

[32]  Van,et al.  A gene-expression signature as a predictor of survival in breast cancer. , 2002, The New England journal of medicine.