Xu Rengyi, Mesaros Clementina, Weng Liwei, Snyder Nathaniel W, Vachani Anil, Blair Ian A, Hwang Wei-Ting
Penn Superfund Research Program & Center of Excellence in Environmental Toxicology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6160, USA.
Department of Biostatistics & Epidemiology, Perelman School of Medicine, University of Pennsylvania, PA, USA.
Biomark Med. 2017 Jul;11(7):547-556. doi: 10.2217/bmm-2017-0087. Epub 2017 May 23.
We compared three statistical methods in selecting a panel of serum lipid biomarkers for mesothelioma and asbestos exposure.
MATERIALS & METHODS: Serum samples from mesothelioma, asbestos-exposed subjects and controls (40 per group) were analyzed. Three variable selection methods were considered: top-ranked predictors from univariate model, stepwise and least absolute shrinkage and selection operator. Crossed-validated area under the receiver operating characteristic curve was used to compare the prediction performance.
Lipids with high crossed-validated area under the curve were identified. Lipid with mass-to-charge ratio of 372.31 was selected by all three methods comparing mesothelioma versus control. Lipids with mass-to-charge ratio of 1464.80 and 329.21 were selected by two models for asbestos exposure versus control.
Different methods selected a similar set of serum lipids. Combining candidate biomarkers can improve prediction.
我们比较了三种统计方法，以选择一组用于间皮瘤和石棉暴露的血清脂质生物标志物。
分析了来自间皮瘤患者、石棉暴露受试者和对照组（每组40例）的血清样本。考虑了三种变量选择方法：单变量模型中的顶级预测因子、逐步回归法以及最小绝对收缩和选择算子法。采用交叉验证的受试者工作特征曲线下面积来比较预测性能。
确定了曲线下交叉验证面积较高的脂质。在比较间皮瘤与对照组时，所有三种方法均选择了质荷比为372.31的脂质。在比较石棉暴露与对照组时，两种模型选择了质荷比为1464.80和329.21的脂质。
不同方法选择了一组相似的血清脂质。组合候选生物标志物可提高预测能力。
