Wang Ping, Lun Yu, Fu Yudong, Wang Fei, Zhao Shihua, Wang Yangyang, Hou Xu
Department of Endocrinology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Oncol Res Treat. 2017;40(10):586-592. doi: 10.1159/000477909. Epub 2017 Sep 12.
Papillary thyroid cancer (PTC) is the most common differentiated thyroid cancer and is responsible for 80-90% of thyroid cancer cases. Despite typically excellent prognoses, these subclinical low-risk cancers are often treated aggressively by surgical thyroidectomy. Consequently, the objective of this study was to generate a prognostic matrix to be used prior to PTC intervention.
In this study, 80 PTC patients were assessed. Following adjustment for sex, logistic regression analysis showed that BRAFV600E mutation, transforming growth factor beta (TGF-β) expression, age, and tumor size are risk factors that can affect tumor clinical stage (p < 0.05). Based on the results of this analysis, we generated a matrix that incorporated 4 variables: patient age, tumor size, BRAFV600E mutation, and TGF-β expression.
We observed that the corresponding area under curve was as high as 0.91. The sensitivity and specificity of the model were 94.74 and 83.61%, respectively. These values are significantly higher than those generated from single indexes.
As a result of this analysis, it is hoped that the resultant matrix can be utilized during clinical diagnosis and treatment prior to thyroid nodule surgery.
甲状腺乳头状癌（PTC）是最常见的分化型甲状腺癌，占甲状腺癌病例的80 - 90%。尽管其预后通常良好，但这些亚临床低风险癌症常通过手术甲状腺切除术进行积极治疗。因此，本研究的目的是生成一个在PTC干预前使用的预后矩阵。
本研究评估了80例PTC患者。在对性别进行调整后，逻辑回归分析表明，BRAFV600E突变、转化生长因子β（TGF-β）表达、年龄和肿瘤大小是可影响肿瘤临床分期的危险因素（p < 0.05）。基于该分析结果，我们生成了一个纳入4个变量的矩阵：患者年龄、肿瘤大小、BRAFV600E突变和TGF-β表达。
我们观察到相应的曲线下面积高达0.91。该模型的敏感性和特异性分别为94.74%和83.61%。这些值显著高于单个指标得出的值。
通过该分析，希望所得矩阵可在甲状腺结节手术前的临床诊断和治疗中使用。
