Gene expression profiling: Does it add predictive accuracy to clinical characteristics in cancer prognosis?
Gene expression profiling: Does it add predictive accuracy to clinical characteristics in cancer prognosis?
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DOI：
10.1016/j.ejca.2006.11.018
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发表时间：
2007-03-01
影响因子：
8.4
通讯作者：
Schemper, Michael
中科院分区：
文献类型：
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作者：
Dunkler, Daniela;Michiels, Stefan;Schemper, Michael
人们普遍认为，基因表达分类器需要进行外部验证，方法是证明它们能够很好地预测其他患者的结果，而不是从分类器的数据中得出的患者。不幸的是，与已确定的临床预后因素相比，分类器的预测准确性的提高通常无法量化。我们的目标是说明为此目的应用适当的统计措施。为了比较仅基于临床因素的模型和基于临床因素加基因分类器的模型的预测准确性，我们计算了预测不准确性的降低和解释变异的比例。这些测量值是针对已发表的基因分类器的三项研究获得的：淋巴瘤患者的生存率、乳腺癌患者的生存率以及头颈癌淋巴结转移的诊断。对于这三项研究，我们的结果表明，由于基因分类器，解释变异和预测准确性存在差异，而且可能很小。因此，未来基因分类器的增益应定期通过适当的统计措施来证明，例如我们推荐的措施。 (c) 2006 Elsevier Ltd. 保留所有权利。
it is widely accepted that gene expression classifiers need to be externally validated by showing that they predict the outcome well enough on other patients than those from whose data the classifier was derived. Unfortunately, the gain in predictive accuracy by the classifier as compared to established clinical prognostic factors often is not quantified. our objective is to illustrate the application of appropriate statistical measures for this purpose. In order to compare the predictive accuracies of a model based on the clinical factors only and of a model based on the clinical factors plus the gene classifier, we compute the decrease in predictive inaccuracy and the proportion of explained variation. These measures have been obtained for three studies of published gene classifiers: for survival of lymphoma patients, for survival of breast cancer patients and for the diagnosis of lymph node metastases in head and neck cancer. For the three studies our results indicate varying and possibly small added explained variation and predictive accuracy due to gene classifiers. Therefore, the gain of future gene classifiers should routinely be demonstrated by appropriate statistical measures, such as the ones we recommend. (c) 2006 Elsevier Ltd. All rights reserved.