The purpose of this study was to retrospectively review the pathologic complete response (pCR) rate from patients (n=86) with stage II and III HER2-positive breast cancer treated with neoadjuvant chemotherapy at our institution from 2008 to 2013 and to determine possible predictive and prognostic factors. Immunohistochemistry for hormone receptors and Ki-67 was carried out. Clinical and pathological features were analyzed as predictive factors of response to therapy. For survival analysis, we used Kaplan-Meier curves to estimate 5-year survival rates and the log-rank test to compare the curves. The addition of trastuzumab to neoadjuvant chemotherapy significantly improved pCR rate from 4.8 to 46.8%, regardless of the number of preoperative trastuzumab cycles (P=0.0012). Stage II patients achieved a higher response rate compared to stage III (P=0.03). The disease-free and overall survivals were not significantly different between the group of patients that received trastuzumab in the neoadjuvant setting (56.3 and 70% at 5 years, respectively) and the group that initiated it post-operatively (75.8 and 88.7% at 5 years, respectively). Axillary pCR post neoadjuvant chemotherapy with trastuzumab was associated with reduced risk of recurrence (HR=0.34; P=0.03) and death (HR=0.21; P=0.02). In conclusion, we confirmed that trastuzumab improves pCR rates and verified that this improvement occurs even with less than four cycles of the drug. Hormone receptors and Ki-67 expressions were not predictive of response in this subset of patients. Axillary pCR clearly denotes prognosis after neoadjuvant target therapy and should be considered to be a marker of resistance, providing an opportunity to investigate new strategies for HER2-positive treatment.

Background Axillary lymph node involvement is one important prognostic factor in breast cancer, but the way to access this information has been modified over the years. This study evaluated if axillary ultrasound (US) coupled with fine-needle aspiration cytology (FNAC) can accurately predict clinically relevant node metastasis in patients with breast cancer, and thus assist clinical decisions Methods This is a cross-sectional study with retrospective data collection of 241 individuals (239 women and 2 men) with unilateral operable breast cancer who were submitted to preoperative axillary assessment by physical exam, US and FNAC if suspicious nodes by imaging. We calculated sensitivity, specificity, and accuracy of the methods. We compared the patient's characteristics using chi-square test, parametrics and non-parametrics statistics according to the variable. Results The most sensible method was US (0.59; 95% CI, 0.50–0.69), and the most specific was US coupled with FNAC (0.97; 95% CI, 0.92–0.99). Only 2.7% of the patients with normal axillary US had more than 2 metastatic nodes in the axillary lymph node dissection, against 50% of the patients with suspicious lymph nodes in the US and positive FNAC. Conclusions Axillary US coupled with FNAC can sort patients who have a few metastatic nodes at most from those with heavy axillary burden and could be one more tool to initially evaluate patients and define treatment strategies.

Breast cancer is the second most common type of cancer in the world (World Cancer Report, 2014 a, b). The evolution of breast cancer treatment usually allows a longer life of patients as well in many cases a relapse of the disease. Usually medical researchers are interested to analyze data denoting the time until the occurrence of an event of interest such as the time of death by cancer in presence of right censored data and some covariates. In some situations, we could have two lifetimes associated to the same patient, as for example, the time free of the disease until recurrence and the total lifetime of the patient. In this case, it is important to assume a bivariate lifetime distribution which describes the possible dependence between the two observations. We consider as an application, different parametric bivariate lifetime distributions to analyze a breast cancer data set considering continuous or discrete data. Inferences of interest are obtained under a statistical Bayesian approach. We get the posterior summaries of interest using existing MCMC (Markov Chain Monte Carlo) methods. The main goal of the study, is to compare the bivariate continuous and discrete distributions that better describes the breast cancer lifetimes.