Breast reconstruction cases increased over the 15 years with the change of paradigm. Most strikingly, prosthesis-based reconstruction rapidly gained its prevalence and became the most common strategy. NSM was only performed for highly selected patients. Patients with breast reconstruction were able to achieve satisfactory loco-regional control in our cohort.

BackgroundThyroid cancer (TC) is one of the most commonly seen secondary malignancy in breast cancer (BC) survivors.Materials and methodsA retrospective study was conducted in BC patients in our center from 1999 to 2013. Patients were divided into BC‐TC group and BC‐alone group.ResultsIn total, 13 978 BC patients were identified, among whom 247 (1.8%) had TC. The standardized incidence ratio (SIR) of TC was 4.48 compared with Chinese females, and up to 98.0% of cases were thyroid papillary carcinomas. A family history of malignancy was the only independent risk factor (odds ratio = 1.457, P = 0.025) for development of TC in patients with BC. We also identified inferior survival in patients with synchronous versus metachronous BC‐TC (P = 0.016). Synchronous BC‐TC (risk ratio = 5.597, P = 0.018) was an independent prognostic factor for inferior RFS.ConclusionsWe observed high co‐occurrence of TC in patients with BC. There might be different mechanisms behind synchronous and metachronous BC‐TC.

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Background: The aim of this study was to develop and validate prognostic nomograms predicting overall (OS) and cancer-specific survival (CSS) of patients with major salivary gland (MaSG) mucoepidermoid carcinoma (MEC). Methods: 1398 MaSG-MEC patients were identified from the Surveillance, Epidemiology and End Results (SEER) database. They were randomly and equally divided into a training cohort (n=699) and a validation cohort (n=699). The best subsets of covariates were identified to develop nomograms predicting OS and CSS based on the smallest Akaike Information Criterion (AIC) value in the multivariate Cox models. The nomograms were internally and externally validated by the bootstrap resampling method. The predictive ability was evaluated by Harrell's Concordance Index (C-index). Results: For the training cohort, eight (age at diagnosis, tumor grade, primary site, surgery, radiation, T, N and M classification) and seven predictors (all the above factors except primary site) were selected to create the nomograms estimating the 3- and 5- year OS and CSS, respectively. C-index indicated better predictive performance of the nomograms than the 7th AJCC staging system, which was confirmed by both internal ( via the training cohort: OS: 0.888 vs 0.785, CSS: 0.938 vs 0.821) and external validation ( via the validation cohort: OS: 0.844 vs 0.743, CSS: 0.882 vs 0.787). The calibration plots also revealed good agreements between the nomogram-based prediction and observed survival. Conclusions: We have proposed and validated the nomograms predicting OS and CSS of MaSG-MEC. They are proved to be of higher predictive value than the AJCC staging system and may be adopted in future clinical practice.