国家神经系统疾病临床医学研究中心数据管理与共享系统

Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases

《国家中心数据管理与共享系统操作说明书 —— 研究者部分》

Predicting the regrowth of clinically non-functioning pituitary adenoma with a statistical model

第一作者：Cheng Sen,Wu Jiaqi

通讯作者：Ying Xiaomin,Zhang Yazhuo

Clinically non-functioning pituitary adenoma; Pred

基本信息

2019-05-20

已发表文章

发表杂志：Journal of Translational Medicine

发表类型: Research Article

影响因子(IF): 5.531

PMID: 31109334 Pubmed原文链接 全文下载

主要研究背景及目的

方法

Tumour samples were collected from 295 patients with NFPA from Beijing Tiantan Hospital. The expression levels of 41 tumour-associated proteins were assessed using tissue microarray analyses. Clinical characteristics were analysed via univariate and multivariate logistic regression analyses. Logistic regression algorithm was applied to build a prediction model based on the expression levels of selected proteins and clinical signatures, which was then assessed in the testing set.

结论

The prediction model could effectively predict the regrowth of NFPA, which may facilitate the prognostic evaluation and guide early interventions.

主要结果

Three proteins and two clinical signatures were confirmed to be significantly related to the regrowth of NFPA, including cyclin-dependent kinase inhibitor 2A (CDKN2A/p16), WNT inhibitory factor 1 (WIF1), tumour growth factor beta (TGF-β), age and tumour volume. A prediction model was generated on the training set, which achieved a fivefold predictive accuracy of 81.2%. The prediction ability was validated on the testing set with an accuracy of 83.9%. The area under the receiver operating characteristic curves (AUC) for the signatures were 0.895 and 0.881 in the training and testing sets, respectively.