Institut für Pathologie, Charité - Universitätsmedizin Berlin, Berlin, Germany.
PLoS One. 2012;7(12):e51862. doi: 10.1371/journal.pone.0051862. Epub 2012 Dec 14.
Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.
基因或蛋白质表达数据通常由度量或至少有序变量表示。为了将连续变量转化为临床决策,需要确定一个截止值,并将患者分为需要不同治疗的两组。目前,没有用于生物标志物截止值确定的标准方法或标准软件。因此,我们开发了 Cutoff Finder,这是一套用于截止值确定的优化和可视化方法,可在线访问。虽然一种截止值优化方法仅基于所研究标志物的分布,但其他方法则优化了二分法与结果或生存变量的相关性。我们通过分析乳腺癌组织中雌激素受体 (ER) 和孕激素受体 (PgR) 的基因表达来说明 Cutoff Finder 的功能。分析并关联了这些重要标志物的分布与免疫组织学确定的 ER 状态和无远处转移生存。Cutoff Finder 有望填补可用生物计量软件库中的一个相关空白,并能更快地优化新的诊断生物标志物。该工具可在 http://molpath.charite.de/cutoff 访问。