构建用于预测喉癌复发的 10 基因预后评分模型。
Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer.
机构信息
Department of Gastroenterology, Harbin Institute of Technology Heilongjiang Hospital, 82 Zhongshan Road, Harbin, 150036, Heilongjiang, People's Republic of China.
Department of Otorhinolaryngology, Heilongjiang Provincial Hospital Affiliated to Harbin Institute of Technology, 82 Zhongshan Road, Harbin, 150036, Heilongjiang, People's Republic of China.
出版信息
Eur J Med Res. 2022 Nov 14;27(1):249. doi: 10.1186/s40001-022-00829-2.
We constructed a prognostic score (PS) model to predict the recurrence risk in patients previously diagnosed with laryngeal cancer (LC). Here the training dataset, consisting of 82 LC samples, was downloaded from The Cancer Genome Atlas (TCGA). The PS model then divided the LC samples into high- and low-risk groups, which predicted well the survival time of LC in three datasets (TCGA dataset: AUC = 0.899; GSE27020: AUC = 0.719; and GSE25727: AUC = 0.662). Therefore, the PS model based on the 10 genes and its nomogram is proposed to help predict the recurrence risk in patients with LC.
我们构建了一个预后评分（PS）模型，以预测先前被诊断为喉癌（LC）的患者的复发风险。在这里，训练数据集由 82 个 LC 样本组成，从癌症基因组图谱（TCGA）下载。该 PS 模型随后将 LC 样本分为高风险和低风险组，在三个数据集（TCGA 数据集：AUC=0.899；GSE27020：AUC=0.719；和 GSE25727：AUC=0.662）中很好地预测了 LC 的生存时间。因此，提出了基于 10 个基因的 PS 模型及其列线图，以帮助预测 LC 患者的复发风险。
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