医学
仿形(计算机编程)
子宫内膜癌
分类
临床试验
佐剂
疾病
肿瘤科
生物信息学
计算生物学
内科学
癌症
计算机科学
人工智能
生物
操作系统
作者
Amy Jamieson,Jessica N. McAlpine
出处
期刊:Journal of The National Comprehensive Cancer Network
日期:2023-02-01
卷期号:21 (2): 210-216
被引量:8
标识
DOI:10.6004/jnccn.2022.7096
摘要
Molecular classification provides an objective, reproducible framework for categorization of endometrial cancers (ECs), informing prognosis and selection of therapy. Currently, the uptake of molecular classification, integration in to EC management algorithms, and enrollment in molecular subtype-specific clinical trials lags behind what it could be. Access to molecular testing is not uniform, and subsequent management (surgical, adjuvant therapy) is unacceptably variable. We are in the midst of a critical landscape change in this disease site, with increasing emphasis on the integration of molecular features in EC care that can potentially improve standard of care globally. This article summarizes the rationale for molecular classification of ECs, strategies for implementation in low and high resource settings, and actionable opportunities based on this information.
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