医学
阶段(地层学)
TNM分期系统
乳腺癌
淋巴结
肿瘤科
雌激素受体
癌症
AJCC分段系统
活检
疾病
内科学
放射科
病理
登台系统
古生物学
生物
作者
Gabriel N. Hortobágyi,Stephen B. Edge,Armando E. Giuliano
出处
期刊:American Society of Clinical Oncology educational book
[American Society of Clinical Oncology]
日期:2018-05-01
卷期号: (38): 457-467
被引量:112
摘要
Expanded understanding of biologic factors that modulate the clinical course of malignant disease have led to the gradual integration of biomarkers into staging classifications. The American Joint Committee on Cancer (AJCC) TNM staging system is universally used and has largely displaced other staging classifications for most, although not all, cancers. Many of the chapters of the eighth edition of the AJCC TNM staging system integrated biomarkers with anatomic definitions. The Breast Chapter added estrogen receptor (ER) and progesterone receptor (PR) expression, HER2 expression, and/or amplification and histologic grade to the anatomic assessment of tumor size, regional lymph node involvement, and distant metastases (known as TNM). While preserving an anatomic staging system for continuity and for regions where modern biomarkers are not always available, the eighth edition emphasizes the increased prognostic precision of the clinical prognostic stage groups and the pathologic prognostic stage groups. The clinical prognostic stage groups are applicable to all patients with primary breast cancer before any treatment has been implemented, but require a clinical and imaging evaluation as well as a biopsy with grade and available ER, PR, and HER2 results; the pathologic prognostic stage groups are applicable to all patients treated with complete surgical excision as first treatment and also require a complete pathology report, grade, and ER, PR, and HER2. Applying the pathologic prognostic stage groups to a large database of patients staged by basic TNM groupings changed the stage grouping of almost 40% of patients. Grouping by pathologic prognostic stage groups led to a better prognostic distribution of the group and more precise individual prognostication.
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