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Objectives The survival benefit of postmastectomy radiotherapy (PMRT) has not been fully proven in inflammatory breast cancer (IBC). Thus, in the present research, we aimed at elucidating the effects of PMRT on the survival of IBC patients. Methods Eligible patients were collected from the Surveillance, Epidemiology, and End Results (SEER) dataset between 2010 and 2013. The Kaplan-Meier method along with the log-rank test was utilized for the comparison of both the overall survival (OS) andthe cancer-specific survival (CSS) in patients undergoing PMRT or not. Additionally, multivariate survival analysis of CSS and OS were performed using the Cox proportional hazard model. Results In total, 293 eligible cases were identified, with the median follow-up time of 27 months (range: 5–59 months). After propensity score matching (PSM), 188 patients (94 for each) were classified intothe No-PMRT and the PMRT group. Consequently, significantly higher OS rates were detected in the PMRT group compared with the No-PMRT group prior to PSM (P = 0.034), and significantly higher CSS (P = 0.013) and OS (P = 0.0063) rates were observed following PSM. Furthermore, multivariate analysis revealed thatPMRT [CSS (HR: 0.519, 95% CI [0.287–0.939], P = 0.030); OS (HR: 0.480, 95% CI [0.269–0.859], P = 0.013)], as well as Her2+/HR+ subtype, was independent favorable prognostic factors.Besides, black ethnicity, AJCC stage IV and triple-negative subtype were independent unfavorable prognostic factors. Further subgroup analysis revealed that most of the study population could benefit from PMRT, no matter OS or CSS. Conclusions Our findings support that PMRT could improve the survival of IBC patients.

Objective The study was designed to construct and validate a nomogram for predicting overall survival (OS) of male breast cancer (MBC) patients with infiltrating duct carcinoma (IDC). Methods The cohort was selected from the Surveillance, Epidemiology, and End Results (SEER) database between January 1, 2004 and December 31, 2013. Univariate and multivariate Cox proportional hazard (PH) regression models were performed. A nomogram was developed based on the significant prognostic indicators of OS. The discriminatory and predictive capacities of nomogram were assessed by Harrell’s concordance index (C-index), calibration plots, area under the curve (AUC) and the decision curve analysis (DCA). Results The median and maximal survival time of 1862 eligible patients were 49 and 131 months, respectively. Multivariate analysis showed that age (P

Background This study was designed to investigate the clinicopathological characteristics, treatment and survival of patients with pulmonary large cell neuroendocrine carcinoma (LCNEC). Methods The Surveillance, Epidemiology and End Results database was utilized to identify patients diagnosed with pulmonary LCNEC between 2004 and 2013. Kaplan–Meier analysis was conducted to determine the overall survival (OS) and cancer-specific survival (CSS) rate. Univariate survival analysis along with log-rank test, and Cox proportional hazards model were employed to detect independent prognostic factors. Results Pulmonary LCNEC accounted for 0.58% (2972/510607) of the total number of lung and bronchus carcinoma. And a total of 1,530 eligible cases were identified, with the median follow-up time of 11 months. To be specific, the 3-, 5-year OS and CSS rates were 22.8%, 16.8% and 26.5%, 20.8% respectively. Generally, pulmonary LCNEC was commonly detected in the elderly (72.2%), males (55.9%), the upper lobe (62.0%) and advanced AJCC stage (65.5%). Multivariate analysis revealed that elderly [(≥60 and