结核病患者药物性肝损伤预警模型的建立及验证研究

摘要/Abstract

摘要： 目的建立并验证预测结核病患者服用固定剂量复合制剂后药物性肝损害发生的预测模型。方法选取208例肝损伤患者,随机分为建模样本156例和验证样本52例,建模样本用于单因素及Logistic回归分析,以寻找影响肝损害发生的影响因素,根据Logistic回归分析结果建立不同的肝损伤预警模型,通过计算ROC曲线下面积检测模型性能。验证样本用于计算不同预警模型的肝损害发生的准确率、敏感度和特异度。结果 Logistic回归分析结果显示居住环境、工作环境和诊断结果是肝损伤发生的影响因素。根据分析结果和专业性,经过比较分析,通过居住环境、工作环境、诊断结果和年龄建立的肝损害预测模型性能良好（偏卡方检验,P>0.05,ROC曲线下面积为0.884）。验证样本预测肝损害发生的准确率为84.6%,敏感度为55.56%,特异度为93.02%。结论通过居住环境、工作环境、诊断结果和年龄建立的肝损害预测模型可以早期、简单且准确地预测结核病患者服用固定剂量复合制剂后药物性肝损害的发生风险,可用于辅助临床决策的制定。

关键词: 结核病, 药物性肝损伤, 固定剂量复合制剂, 预测模型, 验证

Abstract: Objective To develop and validate prognostic models for tuberculosis patients who had the fixed dose compound preparation with drug-induced liver injury.Methods The clinical data of 208 patients with drug-induced liver injury were collected to develop prognostic models．The patients were randomly divided into the modeling sampling group (n=156)and the validation sampling group (n=56). Modeling sampling were used for univariate and Logistic regression analysis to identify factors related with drug-induced liver injury. According to univariate and Logistic regression analysis results, a prognostic model was established. The validation sampling was used to compute the accuracy, sensitivity and specificity of the prognostic models.Result Logistic regression analysis revealed that living environment,working environment and the diagnose result were independent risk factors for drug-induced liver injury．The prognostic model based on the risk factors of admission had favorable performance (P>0.05 for Partial chi square test,0.884 for AUC). The accuracy of the prognostic model was 84.6%, sensitivity was 55.56% and specificity was 93.02%.Conclusion The established model,which is convenient to manage,can timely and accurately predict the prognosis of tuberculosis patients with drug- induced liver injury,and can help in decision-making in clinics.

Key words: Tuberculosis, Drug-induced liver injury, Fixed-dose combination, Prognostic models, Validation

何俊其, 张立民, 郭艳红. 结核病患者药物性肝损伤预警模型的建立及验证研究[J]. 新发传染病电子杂志, 2019, 4(2): 117-120.

HE Jun-qi, ZHANG Li-min, GUO Yan-hong. Development and validation of prognostic models for tuberculosis patients with drug-induced liver injury[J]. Electronic Journal of Emerging Infectious Diseases, 2019, 4(2): 117-120.

参考文献

[1] The promise and reality of fixed-dose combinations with rifampicin. A joint statement of the International Union Against Tuberculosis and Lung Disease and the Tuberculosis Programme of the World Health Organization[J].Tuber Lung Dis,1994,75(3):180-181.
[2] Eisenberg DM, Davis RB, Ettner SL, Appel S, Wilkey S, Van Rompay M, et al.Trends in alternative medicine use in the United States, 1990-1997: results of a follow-up national survey[J]. JAMA, 1998, 280(18):1569-1575.
[3] 夏愔愔,詹思延.国内抗结核药物不良反应发生率的综合分析[J].中华结核和呼吸杂志,2007,30(6):419-423.
[4] The Global Plan to Stlp TB. 2006-2015.Actions for life: towards a world free of tuberculosis[J].Int J Tuberc Lung Dis, 2006, 10(3):240-241.
[5] Zignol M, Hosseini MS, Wright A, et al.Global incidence of multi-drug resistant tuberculosis[J].J Infect Dis, 2006,194(4):479-485.
[6] Lee KL,PryorDB,Harrell FE Jr,et al.Predicting outcome in coronary disease. Statistical models versus expert clinicians[J]. Am JMed,1986,80( 4) : 553-560.
[7] 邱济海,侯巍,杨亦德,等.抗结核药物所致肝损害的特点及危险因素研究[J].中国高等医学教育,2017(01):136-137.
[8] 李文红,王芳,付莹,等.肺结核药物性肝损害的相关因素分析[J].临床肺科杂志,2016,21(11):2097-2100.
[9] Devarbhavi H,Dierkhising R,Kremers WK,et al.Single-center experience with drug-induced liver injury from India: causes,out-come,prognosis,and predictors of mortality[J].Am J Gastroenterol,2010,105(11):2396-2404.
[10] 杨莹. 肺结核病患者抗结核肝损害92例临床分析[J].中国热带医学,2014,14(7): 862-865.
[11] 倪艳,邹永胜,刘泽明.肺结核患者抗结核药物引起肝损害的临床特点分析[J].国外医药抗生素分册,2014,35(2):85-87.
[12] 张娟娟,王云霞,刘振扬,等.影响肺结核病病人防治效果的社会因素分析[J].中国社会医学杂志,2018,35(3):256-258.
[13] Gaude GS,Chaudhury A,Hattiholi J.Drug-induced hepatitis pa-tients[J]. J Family Med Prim Care,2015,4(2):238-243.
[14] Begun M, Newall AT, Marks GB,et al.Contact tracing of tuberculosis: a systematic review of transmission modelling studies[J]. PLoS One, 2013, 8(9): e72470.
[15] Andrews JR, Morrow C, Walensky RP, et al.Integrating social contact and environmental data in evaluating tuberculosis transmission in a South African township[J]. J Infect Dis, 2014, 210(4): 597-603.