Janes Holly, Brown Marshall D, Huang Ying, Pepe Margaret S
Int J Biostat. 2014;10(1):99-121. doi: 10.1515/ijb-2012-0052.
Despite the heightened interest in developing biomarkers predicting treatment response that are used to optimize patient treatment decisions, there has been relatively little development of statistical methodology to evaluate these markers. There is currently no unified statistical framework for marker evaluation. This paper proposes a suite of descriptive and inferential methods designed to evaluate individual markers and to compare candidate markers. An R software package has been developed which implements these methods. Their utility is illustrated in the breast cancer treatment context, where candidate markers are evaluated for their ability to identify a subset of women who do not benefit from adjuvant chemotherapy and can therefore avoid its toxicity.
尽管人们对开发预测治疗反应的生物标志物以优化患者治疗决策的兴趣日益浓厚，但用于评估这些标志物的统计方法的发展相对较少。目前尚无用于标志物评估的统一统计框架。本文提出了一套描述性和推断性方法，旨在评估单个标志物并比较候选标志物。已开发出一个R软件包来实现这些方法。在乳腺癌治疗背景下展示了它们的实用性，其中评估候选标志物识别那些无法从辅助化疗中获益从而可避免其毒性的女性亚组的能力。
