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logistic回归模型在抗甲状腺药物治疗Graves病的预后估价
Evaluation of a logistic Regression Model in Predicting the Prognosis of Graves’ Disease Treated by Antithyroid Drugs
【摘要】 对111例Graves病初发患者用他巴唑治疗6月,停药后随访1年。根据病人一般临床及生化特征,用logistic回归分析法,建立了一个具有4个指标的数学预测模型,其预测停药后1年的预后,具有较高的敏感性(81.5%)和特异性(84.8%),符合率达82.9%(92/111),其结果优于本资料中任何有预测意义的单因素分析。
【Abstract】 One hundred and twelvenew cases of Graves′disease were treatedby tapazole for 6 monsths and followed upfor another 12 months. The initial dosewas 30 mg/d. Clinical and biochemical eu-thyroidism was achieved within 1 to 3months, then a maintenance was givenuntil cessation of drugs at 6 mouths.Onehundred and eleven cases completedthe study. Remission and relapse weredefined at the end of follow-up for 1 yearaccording to the presence or absence ofclinical manifestation of hyperthyroidismand the levels of T3 and T4. The results of the 12-month follow-upShowed that 46 of 111 cases were in remis-sion, and the remaining 65 cases sufferedrelapse. A logistic regression model with4 variables was established, which includ-ed thyroid suppression rate and goitre sizeby palpation at the end of drug treat-ment, the level of T3 before therapy,and the patients′age. The model had 81.5%sensitivity, 84.8% specificity and 82. 9%(92/111) accuracy in predicting the out-come of Graves′disease after withdrawalof drug for 1 year. The results were muchbetter than any other univariate analysisin this study.
【Key words】 Graves’ disease; Drug treatment; logistic regression model; Estimation of prognosis;
- 【文献出处】 华西医科大学学报 , 编辑部邮箱 ,1991年03期
- 【被引频次】1
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