scholarly journals Clinical and Therapeutic Factors Vary by Prognosis in Patients with Pathological Complete Response After Neoadjuvant Therapy for Breast Cancer

2021 ◽  
Vol Volume 13 ◽  
pp. 9235-9246
Author(s):  
Zhenfeng Huang ◽  
Shiyang Jin ◽  
Mengyao Zeng ◽  
Jing Shu ◽  
Yang Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Pathological Complete Response ◽  
Complete Response ◽  
Therapeutic Factors

Cardiac safety and efficacy of concomitant liposomal doxorubicin, docetaxel, and trastuzumab as neoadjuvant therapy in HER2-overexpressing breast cancer: A retrospective analysis.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 583-583
Author(s):  
Christine Brunner ◽  
Thomas Jaeger ◽  
Christoph Suppan ◽  
Elisabeth Mueller-Holzner ◽  
Zerina Jasarevic ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Liposomal Doxorubicin ◽  
Pathological Complete Response ◽  
Neoadjuvant Treatment ◽  
Complete Response ◽  
Left Ventricular Ejection ◽  
Cardiac Safety ◽  
Multicenter Analysis

583 Background: Concurrent therapy of trastuzumab, anthracycline and taxane for the neoadjuvant treatment of breast cancer (BC) results in an improved rate of pathological complete response (pCR). However, there is considerable concern about the cardiac safety of this combination. The use of liposomal doxorubicin might be a valuable alternative with lower cardiotoxicity. We report cardiac safety and pCR-rate of a single arm, retrospective, multicenter analysis of neoadjuvant treatment for BC with liposomal doxorubicin, trastuzumab, and docetaxel. Methods: In this study 84 women with BC and HER2 overexpression were investigated in 3 oncological departments in Austria. All patients were treated with liposomal doxorubicin (50 - 60 mg/m²), docetaxel (75 mg/m²) and concurrent with trastuzumab for 6 cycles as neoadjuvant therapy. All patients were free of cardiovascular disease and had a left ventricular ejection fraction (LVEF) of ≥ 55%. Cardiac function was by LVEF and was examined at regular intervals(cycles 0-3, cycle 6, FU). Clinical response was evaluated by diagnostic breast imaging after cycles 3 and 6. All patients underwent surgery after neoadjuvant chemotherapy. The absence of any residual invasive cancer in the breast and axilla was defined as pathological complete response (pCR). Median follow up was 2.4 years. Results: Median age of the patients was 50 years. After 6 cycles of treatment the pCR rate was 46%. In this cohort a negative estrogen-and/or progesteron receptor was predictive for pCR (p<0.001). No patient progressed during treatment. None of the patients suffered symptomatic heart failure. Only one patient (1.6%) with asymptomatic LVEF of 45% was observed during follow-up. Conclusions: In this multicenter analysis we observed a considerably high rate of pCR in HER2-positive BC treated with liposomal doxorubicin, docetaxel and trastuzumab. The addition of liposomal doxorubicin instead of conventional doxorubicin or epirubicin entails a very favorable cardiotoxicity profile. This regimen is a safe treatment option in patients with HER-2 positive breast cancer.

scholarly journals A microRNA signature associated with pathological complete response to novel neoadjuvant therapy regimen in triple-negative breast cancer

Tumor Biology ◽  
2017 ◽  
Vol 39 (6) ◽  
pp. 101042831770289 ◽  
Author(s):  
Raúl García-Vazquez ◽  
Erika Ruiz-García ◽  
Abelardo Meneses García ◽  
Horacio Astudillo-de la Vega ◽  
Fernando Lara-Medina ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Pathological Complete Response ◽  
Complete Response ◽  
Therapy Regimen

scholarly journals Radiomics Analysis of Multi-Phase DCE-MRI in Predicting Tumor Response to Neoadjuvant Therapy in Breast Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2086
Author(s):  
Shuyi Peng ◽  
Leqing Chen ◽  
Juan Tao ◽  
Jie Liu ◽  
Wenying Zhu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Tumor Response ◽  
Pathological Complete Response ◽  
Complete Response ◽  
Imaging Features ◽  
Dynamic Contrast Enhancement ◽  
Post Contrast ◽  
Dce Mri ◽  
Five Phases

Objective: To explore whether the pretreatment dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and radiomics signatures were associated with pathologic complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer. Method: A retrospective review of 70 patients with breast invasive carcinomas proved by biopsy between June 2017 and October 2020 (26 patients were pathological complete response, and 44 patients were non-pathological complete response). Within the pre-contrast and five post-contrast dynamic series, a total of 1037 quantitative imaging features were extracted from in each phase. Additionally, the Δfeatures (the difference between the features before and after the comparison) were used for subsequent analysis. The least absolute shrinkage and selection operator (LASSO) regression method was used to select features related to pCR, and then use these features to train multiple machine learning classifiers to predict the probability of pCR for a given patient. The area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the predictive performances of the radiomics model for each of the five phases of time points. Result: Among the five phases, each individual phase performed with AUCs ranging from 0.845 to 0.919 in predicting pCR. The best single phases performance was given by the 3rd phase (AUC = 0.919, sensitivity 0.885, specificity 0.864). 5 of the features have significant differences between pCR and non-pCR groups in each phase, most features reach their maximum or minimum in the 2nd or 3rd phase. Conclusion: The radiomic features extracted from each phase of pre-treatment DCE-MRI possess discriminatory power to predict tumor response.

scholarly journals Value of Machine Learning with CE-MRI Radiomics for Early Prediction of Pathological Complete Response to Neoadjuvant Therapy in HER2-positive Invasive Breast Cancer

2020 ◽  
Author(s):  
Qin Li ◽  
Qin Xiao ◽  
Jianwei Li ◽  
Zhe Wang ◽  
He Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Neoadjuvant Therapy ◽  
Invasive Breast Cancer ◽  
Pathological Complete Response ◽  
Complete Response ◽  
Early Prediction ◽  
Her2 Positive ◽  
Invasive Approach ◽  
Linear Svm

Abstract Backgrouds To assess the value of radiomics based on multiphases contrast-enhanced magnetic resonance imaging(CE-MRI) for early prediction of pathological complete response(pCR) to neoadjuvant therapy(NAT) in patients with human epithelial growth factor receptor 2(HER2) positive invasive breast cancer.Methods A total of 127 patients with newly diagnosed primary HER2 positive invasive breast cancer underwent CE-MRI before NAT and performed surgery after NAT. Radiomic features were extracted from the 1st postcontrast CE-MRI phase(CE1) and multi-phases CE-MRI(CEm). With selected features using a forward stepwise regression, 23 machine learning classifiers based on CE1 and CEm were constructed respectively. The performence of classifiers were assessed and compared. Results For the task of pCR classification, 6 radiomic features from CE1 and 6 from CEm were selected for the final machine learning models respectively. The linear SVM based on CEm outperformed the Logistic regression model using CE1 with an AUC of 0.84 vers 0.69. In mass and non-mass enhancement groups, the accuracy of linear SVM achieved 76% and 84%. Whereas in unifocal and unilateral multifocal cases, 79% and 75% accuracy were achieved by linear SVM. Conclusion Multiphases CE-MRI imaging may offer more heterogeneity information in the tumor and provide a non-invasive approach for early prediction of pCR to NAT in patients with HER2 positive invasive breast cancer.

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