A High-Accuracy Model Based on Plasma miRNAs Diagnoses Intrahepatic Cholangiocarcinoma: A Single Center with 1001 Samples.
A High-Accuracy Model Based on Plasma miRNAs Diagnoses Intrahepatic Cholangiocarcinoma: A Single Center with 1001 Samples.
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基于血浆 miRNA 的高精度模型诊断肝内胆管癌：单中心 1001 个样本。
DOI：
10.3390/diagnostics11040610
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发表时间：
2021-03-29
期刊：
影响因子：
--
通讯作者：
Zhou J
中科院分区：
文献类型：
--
作者：
Hu J;Wang YN;Song DJ;Tan JP;Cao Y;Fan J;Wang Z;Zhou J
目的：肝内胆管细胞癌（Intrahepatic cholangiocarcinoma，iCCA）是一种高度恶性肿瘤。超过70%的患者在晚期被诊断出来。本研究旨在评价血浆miR-21、miR-122和CA 19 -9对iCCA的诊断价值，以期建立一种新的模型，提高iCCA的诊断准确性。材料与方法：在359例iCCA患者和642例对照（健康、良性肝脏病变、其他恶性肝脏肿瘤）中检测血浆miR-21和miR-122。所有1001份样本按时间顺序分配至训练队列（n = 668）和验证队列（n = 333）。应用逻辑回归模型将这些标记物联合收割机组合。以受试者工作特征曲线下面积（AUC）作为准确性指标评价诊断性能。结果：iCCA患者血浆miR-21和miR-122水平显著高于对照组。较高的血浆miR-21水平与较大的肿瘤大小显著相关（p = 0.030）。通过使用miR-21、miR-122和CA 19 -9构建三标记物模型，其显示AUC为0.853（95%CI：0.824-0.879;灵敏度：73.0%，特异性：87.4%）以区分iCCA与对照。这些结果随后在验证队列中得到证实，AUC为0.866（0.825-0.901）。诊断早期（0-I期）iCCA患者（AUC：0.848）和CA 19 - 9阴性iCCA患者（AUC：0.795）的结果相似。结论：我们建立了一个新的三标记模型，具有高精度的基础上大量的参与者，以区分iCCA从控制。该模型对早期iCCA和CA 19 - 9阴性iCCA的诊断具有重要的临床应用价值。
Objectives: Intrahepatic cholangiocarcinoma (iCCA) is a highly malignant cancer. More than 70% of patients are diagnosed at an advanced stage. The aim of this study was to evaluate the diagnostic value of plasma miR-21, miR-122, and CA19-9, hoping to establish a novel model to improve the accuracy for diagnosing iCCA. Materials and methods: Plasma miR-21 and miR-122 were detected in 359 iCCA patients and 642 controls (healthy, benign liver lesions, other malignant liver tumors). All 1001 samples were allocated to training cohort (n = 668) and validation cohort (n = 333) in a chronological order. A logistic regression model was applied to combine these markers. Area under the receiver operating characteristic curve (AUC) was used as an accuracy index to evaluate the diagnostic performance. Results: Plasma miR-21 and miR-122 were significantly higher in iCCA patients than those in controls. Higher plasma miR-21 level was significantly correlated with larger tumor size (p = 0.030). A three-marker model was constructed by using miR-21, miR-122 and CA19-9, which showed an AUC of 0.853 (95% CI: 0.824–0.879; sensitivity: 73.0%, specificity: 87.4%) to differentiate iCCA from controls. These results were subsequently confirmed in the validation cohort with an AUC of 0.866 (0.825–0.901). The results were similar for diagnosing early (stages 0–I) iCCA patients (AUC: 0.848) and CA19-9negative iCCA patients (AUC: 0.795). Conclusions: We established a novel three-marker model with a high accuracy based on a large number of participants to differentiate iCCA from controls. This model showed a great clinical value especially for the diagnosis of early iCCA and CA19-9negative iCCA.
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影响因子：
25.7
作者：
Beyoglu, Diren;Idle, Jeffrey R.
通讯作者：
Idle, Jeffrey R.
影响因子：
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作者：
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通讯作者：
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DOI：
10.1158/1541-7786.mcr-13-0419
发表时间：
2014-06
期刊：
Molecular cancer research : MCR
影响因子：
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通讯作者：
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作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
Roderburg, Christoph