A diagnostic model to differentiate simple steatosis from nonalcoholic steatohepatitis based on the likelihood ratio form of Bayes theorem
A diagnostic model to differentiate simple steatosis from nonalcoholic steatohepatitis based on the likelihood ratio form of Bayes theorem
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DOI：
10.1016/j.clinbiochem.2008.11.005
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发表时间：
2009-05-01
影响因子：
2.8
通讯作者：
Jose Pirola, Carlos
中科院分区：
文献类型：
--
作者：
Sookoian, Silvia;Castano, Gustavo;Jose Pirola, Carlos
目的：为了评估一个诊断模型的性能的基础上的综合指数，使用临床和实验室数据，包括心血管生物标志物，以帮助医生区分患者与非酒精性脂肪性肝炎（NASH）。设计和方法：101例活检证实的功能，非酒精性脂肪性肝病。我们研究了9种生物标志物在预测组织学疾病严重程度中的作用，包括常规生化检查、C反应蛋白、可溶性细胞间粘附分子-1（sICAM-1）和人体测量学评价。使用受试者工作特征（ROC）曲线和似然比（LR）评价每个检验的拟合度。结果：在一个所有检测结果均为阳性的模型患者中，NASH的检测后概率为99.5%。结论：每个单独的生物标志物独立预测疾病结局的能力低于将每个单独的检测结果的LR相乘后构建的复合指数。(C)2008年加拿大临床化学家协会。爱思唯尔公司出版All rights reserved.
Objective: To evaluate the performance of a diagnostic model based on a composite index using clinical and laboratory data, including cardiovascular biomarkers, to help practitioners to differentiate patients with simple steatosis from those with nonalcoholic steatohepatitis (NASH).Design and methods: 101 patients with biopsy proven features of nonalcoholic fatty liver disease were included. We investigated the usefulness of 9 biomarkers in predicting the histological disease severity, including routine biochemical tests, C-reactive protein, soluble intercellular adhesion molecule-1 (sICAM-1) and anthropometric evaluation. Receiver operating characteristic (ROC) curves and likelihood ratios (LRs) were used to evaluate the fit of each test. A composite index was calculated as the product of each individual test LR.Results: In a model patient who has all positive tests, the post-test probability for NASH would be 99.5%.Conclusion: The capacity of each individual biomarker to independently predict the disease outcome was lower than a composite index constructed after multiplying the LR for each individual test combined into a "multimarker" score. (C) 2008 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.