Gene Expression-Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use?
Gene Expression-Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use?
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DOI：
10.1093/jnci/djq025
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发表时间：
2010-04-07
影响因子：
10.3
通讯作者：
Simon, Richard
中科院分区：
文献类型：
--
作者：
Subramanian, Jyothi;Simon, Richard
大量研究报告了基于基因表达的肺癌预后特征的发展。此类研究的最终目标应该是开发经过充分验证的临床有用的预后特征，以改善治疗决策，超越当前的实践标准。我们严格审查了已发表的研究，报告了基于基因表达的非小细胞肺癌预后特征的发展，以评估实现这一目标所取得的进展。 2002 年 1 月 1 日至 2009 年 2 月 28 日期间发表的研究是通过 PubMed 搜索确定的。对已识别文章的摘要进行手工筛选后，选择了 16 篇相关文章。对这些出版物进行了详细评估，包括研究设计的适当性、独立数据集上预后特征的统计验证、以公正的方式呈现结果，以及证明新特征在使用现有治疗指南之外获得的医疗效用。根据本次审查，我们发现几乎没有证据表明任何报告的基因表达特征已准备好用于临床应用。我们还发现许多研究的设计和分析存在严重问题。我们提出了一套指南来帮助设计、分析和评估预后特征研究。这些指南强调了重点研究计划的重要性，以解决特定的重要医学问题，并使用公正的分析方法来评估所得特征是否提供了超出基于护理的预后因素标准的医疗效用证据。
A substantial number of studies have reported the development of gene expression-based prognostic signatures for lung cancer. The ultimate aim of such studies should be the development of well-validated clinically useful prognostic signatures that improve therapeutic decision making beyond current practice standards. We critically reviewed published studies reporting the development of gene expression-based prognostic signatures for non-small cell lung cancer to assess the progress made toward this objective. Studies published between January 1, 2002, and February 28, 2009, were identified through a PubMed search. Following hand-screening of abstracts of the identified articles, 16 were selected as relevant. Those publications were evaluated in detail for appropriateness of the study design, statistical validation of the prognostic signature on independent datasets, presentation of results in an unbiased manner, and demonstration of medical utility for the new signature beyond that obtained using existing treatment guidelines. Based on this review, we found little evidence that any of the reported gene expression signatures are ready for clinical application. We also found serious problems in the design and analysis of many of the studies. We suggest a set of guidelines to aid the design, analysis, and evaluation of prognostic signature studies. These guidelines emphasize the importance of focused study planning to address specific medically important questions and the use of unbiased analysis methods to evaluate whether the resulting signatures provide evidence of medical utility beyond standard of care-based prognostic factors.