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Using Probability for Pathological Complete Response (pCR) as a Decision Support Marker for Neoadjuvant Chemotherapy in HER2 Negative Breast Cancer Patients – a Survey Among Physicians

机译：利用病理完全反应（PCR）作为HER2阴性乳腺癌患者Neoadjuvant化疗的决策支持标志物 - 医师之间的调查

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Paul Gass; Michael Untch; Volkmar Müller; Volker Möbus; Christoph Thomssen; Lothar Häberle; Ramona Erber; Alexander Hein; Sebastian Jud; Michael Lux; Carolin Hack; Arndt Hartmann; Hans-Christian Kolberg; Johannes Ettl; Diana Lüftner; Christian Jackisch; Matthias Beckmann; Wolfgang Janni; Andreas Schneeweiss; Peter Fasching; Naiba Nabieva;
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1. 基于上皮-间质转化标志物的循环肿瘤细胞表型检测对HER2阴性转移性乳腺癌一线化疗的预后意义 [J] . Xiuwen Guan, Ruigang Cai, Ying Fan, 癌症（英文版） . 2019,第009期
2. Using Probability for Pathological Complete Response (pCR) as a Decision Support Marker for Neoadjuvant Chemotherapy in HER2 Negative Breast Cancer Patients – a Survey Among Physicians [J] . Paul Gass, Michael Untch, Volkmar Müller, Geburtshilfe und Frauenheilkunde . 2018,第7期

机译：利用病理完全反应（PCR）作为HER2阴性乳腺癌患者Neoadjuvant化疗的决策支持标志物 - 医师之间的调查
3. Pathologic complete response (pCR) and prognosis following neoadjuvant chemotherapy plus anti-HER2 therapy of HER2-positive early breast cancer (EBC) [J] . Intelligence: A Multidisciplinary Journal . 2020,第期

机译：病理完全反应（PCR）和Neoadjuvant化疗后预后加上HER2阳性早期乳腺癌的抗HER2治疗（EBC）
4. A model using easily evaluated clinical features to identify triple negative breast cancer (TNBC) patients (pts) with high probability of achieving pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) [J] . Moulder S., Adrada B., Lim B., The Breast : . 2019,第Suppla1期

机译：使用易于评估的临床特征的模型，以鉴定三重阴性乳腺癌（TNBC）患者（PTS），具有实现病理完全反应（PCR）到Neoadjuvant Systemic Therapy（NAST）的高可能性
5. Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Deep Learning with Integrative Imaging, Molecular and Demographic Data [C] . Hongyi Duanmu, Pauline Boning Huang, Srinidhi Brahmavar, International Conference on Medical Image Computing and Computer-Assisted Intervention . 2020

机译：利用综合成像，分子和人口统计数据预测对乳腺癌新辅助化疗的病理完全反应
6. Using Preoperative Mri-guided Biopsies to Predict Pathologic Complete Response after Neoadjuvant Chemotherapy in Breast Cancer [D] . Kim, Jiyoon. 2019

机译：在乳腺癌新辅助化疗后使用术前Mri引导的活检来预测病理完全缓解
7. Evaluation of Pathologic Complete Response (pCR) to Neoadjuvant Chemotherapy in Iranian Breast Cancer Patients with Estrogen Receptor Positive and HER2 Negative and impact of predicting variables on pCR [O] . Ramesh Omranipour, Roghiyeh Jalili, Adel Yazdankhahkenary, 2020

机译：伊朗乳腺癌患者雌激素受体阳性和HER2阴性的新辅助化疗对病理完全缓解（pCR）的评估以及预测变量对pCR的影响
8. Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in ER-Positive, HER2-Negative Breast Cancer Patients [O] . Claudia Mazo, Stephen Barron, Catherine Mooney, 2020

机译：ER-阳性，HER2阴性乳腺癌患者Neoadjuvant化疗病理完全反应的多基因预后签名及预测

Using Probability for Pathological Complete Response (pCR) as a Decision Support Marker for Neoadjuvant Chemotherapy in HER2 Negative Breast Cancer Patients – a Survey Among Physicians

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