Logistic回归分析评价简易无创模型预测乙型肝炎相关肝硬化  

Appraisement of Simple Non-Invasive Models for Predicting Hepatitis B Associated Cirrhosis by Binary Logistic Regression Analysis

作　　者：张占卿[1] 曹婕[1] 陆伟[1] 史连国[1] 

机构地区：[1]复旦大学附属公共卫生临床中心肝病科,上海201508

出　　处：《武汉大学学报（医学版）》2009年第1期93-96,共4页Medical Journal of Wuhan University

基　　金：国家863计划生物和医药技术领域重大/重点项目基金(编号:2006AA02A411)

摘　　要：目的:评价简易无创模型AAR(AST-to-ALT ratio)、APRI(AST-to-platelet ratio index)、SPRI(spleen-to-platelet ratio index)、API(age-platelet index)、ASPRI(age-spleen-to-platelet ratio index)预测乙型肝炎相关肝硬化的临床价值。方法:慢性乙型肝炎170例,其中病理诊断为非肝硬化138例,肝硬化32例。参照原始文献构建预测肝纤维化程度的简易无创模型。统计分析采用SPSS 13.0软件。简易无创模型在非肝硬化与肝硬化患者之间的比较采用两独立样本的t检验。简易无创模型预测肝硬化的评价采用二分类Logistic逐步回归分析。结果:肝硬化患者的平均AAR、SPRI、API、ASPRI显著大于非肝硬化患者(P=0.000,0.009,0.000,0.005),平均APRI相近于非肝硬化患者(P=0.223)。只有AAR和API符合Logistic回归模型纳入自变量标准(P<0.05)。基于简易无创模型建立的Logistic回归模型预测肝硬化的灵敏度、特异度、阳性预测值、阴性预测值、准确度分别为0.22,0.99,0.70,0.84,0.84。结论:AAR和API可能是预测乙型肝炎相关肝硬化较可靠的简易无创模型。基于简易无创模型建立的预测乙型肝炎相关肝硬化的Logistic回归模型有一定的临床实践效能。Objective： To appraise the clinical efficacy of simple non-invasive models of AST-to-ALT ratio （AAR）, AST-to-platelet ratio index （APRI）, spleen-to-platelet ratio index （SPRI）, ageplatelet index （API）, age spleen to-platelet ratio index （ASPRI） for predicting hepatitis B associated cirrhosis. Methods： A total of 170 consecutive patients with chronic hepatitis B were retrospectively studied, in which 138 patients and 32 patients were diagnosed pathologically as non-cirrhosis and cirrhosis. The simple non-invasive models were calculated as described originally. SPSS 13.0 was used for statistical analysis. Independent samples t tests were used for comparisons of the simple non invasive models between patients with and without cirrhosis. Binary logistic stepwise regression analysis was used for appraisement of simple non-invasive models to predict cirrhosis. Results： The average AAR, SPRI, API and ASPRI in patients with cirrhosis were higher significantly than those in patients without cirrhosis （P=0. 000, 0. 009, 0. 000, 0. 005,respectively）, but the average out cirrhosis （P=0. 223）. Of the entry criterion （P〈0. 05） APRI in patients with cirrhosis was similar to that in patients with d API accorded with regression analysis.The sensitivity, logistic regre specificity, ssion model positive predi based on the ctive value, negative simple non-invasive predictive models for associated cirrhosis were 0.22, 0.99, 0.70, 0.84, and 0.84 respectively. value and accuracy of predicting hepatitis B Conclusion： AAR and API could be the reliable simple non invasive models for predicting hepatitis B associated cirrhosis. The logistic regression model based on the simple non invasive models could have clinical efficacy for predicting hepatitis B associated cirrhosis.

关 键 词：无创模型 肝硬化 乙型肝炎 二分类Logistic回归 

分 类 号：R512.62[医药卫生—内科学]