This book deals with the essential factors in the personalization of treatment for primary breast cancer. These include host issues, lymph node surgery, radiation therapy, and preoperative systemic treatment requiring specialized knowledge, multidisciplinary care experience, techniques, and research. Locoregional treatment in conjunction with systemic treatments is another important factor, with options for local therapy significantly affected by genetic BRCA mutation. Axillary treatment issues have become top priorities in recent primary breast cancer care, and these are highlighted in the book's presentation of technological advances in lymph node mapping and diagnosis, axillary clearance in patients with nodal metastasis, and the role of axillary surgery. Attention is also given to locoregional treatment after preoperative systemic therapy. Because therapeutic impact differs depending upon biological characteristics such as tumor subtype, local therapy should be based both on tumor biology and on therapeutic response in parallel. Associated translational research and mathematical prediction tools such as nomograms also are introduced. This book provides the essence of primary breast cancer care, particularly its individualization with novel therapeutic concepts and strategies, and will greatly benefit physicians and clinical investigators in breast cancer institutions.

Covers essential factors in the personalization of treatment for primary breast cancer Comprehensive updated knowledge and future perspectives of primary breast cancer Presents novel therapeutic concepts and strategies for individualized breast cancer care Includes supplementary material: sn.pub/extras

Autorentext

Masakazu Toi, Professor, Breast Surgery, Kyoto University

Eric P Winer, Professor, Department of Medicine, Harvard Medical School

John R Benson, Professor, Cambridge Breast Unit, Cambridge University

Suzanne Klimberg, Breast Surgical Oncology, University of Arkansas for Medical Sciences.

Inhalt

Part I Treatment for the Patients Having Breast Cancer High-Risk.- Chapter I Risk-Reducing Surgery for Breast Cancer Patients with BRCA Mutations.- Chapter 2 Prophylactic Risk Reducing Surgery for Breast Cancer.- Chapter 3 Merits and Demerits of Practice for Hereditary Breast and Ovarian Cancer Syndrome (Advices and Issues).- Part II Axillary Treatment.- Chapter 4 Sentinel Lymph Node Biopsy and Neoadjuvant Chemotherapy in Breast Cancer Patients.- Chapter 5 Axillary Reverse Mapping (ARM) as a Means to Reduce Lymphedema During Sentinel Lymph Node or Axillary Node Dissection.- Chapter 6 Ultrasound for Axillary Staging.- Chapter 7 One Step Nucleic Acid Amplification(OSNA)Assay for Primary Breast Cancer.- Chapter 8 Management of the Clinically Node-Negative Axilla in Primary Breast Cancer.- Chapter 9 Lymphatic Mapping and Optimization of Sentinel Lymph Node Dissection.- Part III Radiation therapy.- Chapter 10 Personalization ofRadiotherapy for Breast Cancer.- Chapter 11 New Technologies in Radiation Therapy.- Chapter 12 Radiotherapy Following Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer.- Part IV Preoperative Hormone Therapy.- Chapter 13 Novel Translational Research of Neoadjuvant Endocrine Therapy.- Chapter 14 Alterations of Biomarkers by Neoadjuvant Endocrine Therapy.- Part V Preoperative chemotherapy.- Chapter 15 Essence of Neoadjuvant Therapy.- Chapter 16 The challenge to Overcome Triple Negative Breast Cancer Heterogeneity.- Chapter 17 Surgical Management of Breast Cancer after Preoperative Systemic Treatment.- Chapter 18 Imaging of Tumor Response by Preoperative Systemic Treatment.- Part VI Preoperative anti-HER2 therapy.- Chapter 19 Human Epidermal Growth Factor Receptor (HER) Family Molecular Structure.- Chapter 20 Locoregional Therapy Following Neoadjuvant Therapy for HER2-Positive Breast Cancer: Opportunities and Challenges.- Part VII Mathematical prediction/assessment model.- Chapter 21 Nomograms to predict positive resection margin and to predict 3 or more positive lymph nodes.- Chapter 22 Practical Use of Nomograms.- Chapter 23 Data Mining and Mathematical Model Development.