精确肿瘤学
精密医学
医学
临床试验
匹配(统计)
医学物理学
决策支持系统
选择(遗传算法)
癌症
肿瘤科
计算机科学
内科学
病理
数据挖掘
人工智能
作者
Katherine C. Kurnit,Ecaterina E. Dumbrava,Beate Litzenburger,Yekaterina B. Khotskaya,Amber M. Johnson,Timothy A. Yap,Jordi Rodón,Jia Zeng,Md Abu Shufean,Ann M. Bailey,Nora Sánchez,Vijaykumar Holla,John Mendelsohn,Kenna M. Shaw,Elmer V. Bernstam,Gordon B. Mills,Funda Meric‐Bernstam
标识
DOI:10.1158/1078-0432.ccr-17-2494
摘要
Abstract With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719–31. ©2018 AACR.
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