113 research outputs found

    Molecular Subtype Classification Is a Determinant of Non-Sentinel Lymph Node Metastasis in Breast Cancer Patients with Positive Sentinel Lymph Nodes

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    Background: Previous studies suggested that the molecular subtypes were strongly associated with sentinel lymph node (SLN) status. The purpose of this study was to determine whether molecular subtype classification was associated with nonsentinel lymph nodes (NSLN) metastasis in patients with a positive SLN. Methodology and Principal Findings: Between January 2001 and March 2011, a total of 130 patients with a positive SLN were recruited. All these patients underwent a complete axillary lymph node dissection. The univariate and multivariate analyses of NSLN metastasis were performed. In univariate and multivariate analyses, large tumor size, macrometastasis and high tumor grade were all significant risk factors of NSLN metastasis in patients with a positive SLN. In univariate analysis, luminal B subgroup showed higher rate of NSLN metastasis than other subgroup (P = 0.027). When other variables were adjusted in multivariate analysis, the molecular subtype classification was a determinant of NSLN metastasis. Relative to triple negative subgroup, both luminal A (P = 0.047) and luminal B (P = 0.010) subgroups showed a higher risk of NSLN metastasis. Otherwise, HER2 over-expression subgroup did not have a higher risk than triple negative subgroup (P = 0.183). The area under the curve (AUC) value was 0.8095 for the Cambridge model. When molecular subtype classification was added to the Cambridge model, the AUC value was 0.8475. Conclusions: Except for other factors, molecular subtype classification was a determinant of NSLN metastasis in patient

    Correlation of exhaled breath temperature with bronchial blood flow in asthma

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    In asthma elevated rates of exhaled breath temperature changes (Δe°T) and bronchial blood flow (Q(aw)) may be due to increased vascularity of the airway mucosa as a result of inflammation. We investigated the relationship of Δe°T with Q(aw )and airway inflammation as assessed by exhaled nitric oxide (NO). We also studied the anti-inflammatory and vasoactive effects of inhaled corticosteroid and β(2)-agonist. Δe°T was confirmed to be elevated (7.27 ± 0.6 Δ°C/s) in 19 asthmatic subjects (mean age ± SEM, 40 ± 6 yr; 6 male, FEV(1 )74 ± 6 % predicted) compared to 16 normal volunteers (4.23 ± 0.41 Δ°C/s, p < 0.01) (30 ± 2 yr) and was significantly increased after salbutamol inhalation in normal subjects (7.8 ± 0.6 Δ°C/ s, p < 0.05) but not in asthmatic patients. Q(aw), measured using an acetylene dilution method was also elevated in patients with asthma compared to normal subjects (49.47 ± 2.06 and 31.56 ± 1.6 μl/ml/min p < 0.01) and correlated with exhaled NO (r = 0.57, p < 0.05) and Δe°T (r = 0.525, p < 0.05). In asthma patients, Q(aw )was reduced 30 minutes after the inhalation of budesonide 400 μg (21.0 ± 2.3 μl/ml/min, p < 0.05) but was not affected by salbutamol. Δe°T correlates with Q(aw )and exhaled NO in asthmatic patients and therefore may reflect airway inflammation, as confirmed by the rapid response to steroids

    Clinicopathologic Features Associated With Having Four or More Metastatic Axillary Nodes in Breast Cancer Patients With a Positive Sentinel Lymph Node

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    The survival benefit of a completion axillary lymph node dissection (ALND) in patients after removal of a metastatic sentinel lymph node (SLN) is uncertain and is under study in ongoing clinical trials. The completion ALND remains necessary, however, for the identification of cases with at least four metastatic lymph nodes, in which extended-field locoregional and/or postmastectomy radiation will be recommended. Our goal was evaluate clinicopathologic features that might serve as surrogates for determining which patients with a positive SLN are likely or unlikely to belong to this high-risk subset.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41409/1/10434_2006_Article_9251.pd

    Microenvironmental Influences that Drive Progression from Benign Breast Disease to Invasive Breast Cancer

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    Invasive breast cancer represents the endpoint of a developmental process that originates in the terminal duct lobular units and is believed to progress through stages of increasing proliferation, atypical hyperplasia, and carcinoma in situ before the cancer acquires invasive and metastatic capabilities. By comparison with invasive breast cancer, which has been studied extensively, the preceding stages of benign breast disease are more poorly understood. Much less is known about the molecular changes underlying benign breast disease development and progression, as well as the transition from in situ into invasive disease. Even less focus has been given to the specific role of stroma in this progression. The reasons for lack of knowledge about these lesions often come from their small size and limited sample availability. More challenges are posed by limitations of the models used to investigate the lesions preceding invasive breast cancer. However, recent studies have identified alterations in stromal cell function that may be critical for disease progression from benign disease to invasive cancer: key functions of myoepithelial cells that maintain tissue structure are lost, while tissue fibroblasts become activated to produce proteases that degrade the extracellular matrix and trigger the invasive cellular phenotype. Gene expression profiling of stromal alterations associated with disease progression has also identified key transcriptional changes that occur early in disease development. In this review, we will summarize recent studies showing how stromal factors can facilitate progression of ductal carcinoma in situ to invasive disease. We also suggest approaches to identify processes that control earlier stages of disease progression

    New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients

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    <p>Abstract</p> <p>Background</p> <p>Current practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model.</p> <p>Methods</p> <p>We constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University.</p> <p>Results</p> <p>285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size.</p> <p>Conclusion</p> <p>We present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets. </p

    Validation of the IBIS breast cancer risk evaluator for women with lobular carcinoma in-situ.

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    BACKGROUND: Management advice for women with lobular carcinoma in situ (LCIS) is hampered by the lack of accurate personalised risk estimates for subsequent invasive breast cancer (BC). Prospective validation of the only tool that estimates individual BC risk for a woman with LCIS, the International Breast Cancer Intervention Study Risk Evaluation Tool (IBIS-RET), is lacking. METHODS: Using population-based cancer registry data for 732 women with LCIS, the calibration and discrimination accuracy of IBIS-RET Version 7.2 were assessed. RESULTS: The mean observed 10-year risk of invasive BC was 14.1% (95% CI:11.3%-17.5%). IBIS-RET overestimated invasive BC risk (p = 0.0003) and demonstrated poor discriminatory accuracy (AUC 0.54, 95% CI: 0.48 - 0.62). CONCLUSIONS: Clinicians should understand that IBIS-RET Version 7.2 may overestimate 10-year invasive BC risk for Australian women with LCIS. The newer IBIS-RET Version 8.0, released September 2017, includes mammographic density and may perform better, but validation is needed
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