摘要
背景 利福平耐药/耐多药结核病(RR/MDR-TB)治疗困难,治愈率低,且传染性强,氟喹诺酮类(FQs)作为治疗RR/MDR-TB的核心药物,耐药趋势严峻,对FQs影响因素进行分析有助于提高RR/MDR-TB的治愈率,并控制准广泛耐药(pre-XDR)和广泛耐药结核病的发生.目的 分析住院肺结核患者FQs耐药情况及影响因素,构建FQs耐药危险因素的列线图(Nomogram)预测模型并进行验证.方法 回顾性选取于 2021 年 1 月—2022 年2 月在贵阳市公共卫生救治中心住院且有药物敏感试验结果的 583 例肺结核患者为研究对象.根据治疗史将患者分为初治组(296例)和复治组(287例);根据FQs耐药情况将患者分为FQs耐药组(63例)和FQs敏感组(520例).分析患者对 13 种抗结核药物总耐药分布情况,比较FQs耐药组与FQs敏感组肺结核患者的基线特征.采用LASSO回归模型筛选特征变量后,行多因素Logistic回归分析FQs耐药的独立危险因素,并构建Nomogram预测模型;采用受试者工作特征(ROC)曲线下面积(AUC)、校准曲线对其进行验证.结果 583 例患者中FQs敏感 520 例,耐药 63 例,耐药率为 10.81%,仅次于一线抗结核药异烟肼、利福平、链霉素、乙胺丁醇总耐药率(36.36%、32.76%、21.61%、12.86%).复治组患者利福平、异烟肼、乙胺丁醇、链霉素、左氧氟沙星、莫西沙星、利福平耐药(RR)、耐多药(MDR)、pre-XDR耐药率高于初治组(P<0.05).FQs耐药组患者其他民族、复治、艾滋病、吸毒史、空洞、咯血、不规则抗结核史、MDR占比高于FQs敏感组(P<0.05).LASSO回归筛选出 6 个变量:民族、治疗史、艾滋病、吸毒史、咯血、MDR;多因素Logistic回归分析结果显示,其他民族(OR=2.313,95%CI=1.153～4.640,P=0.018)、复治(OR=1.892,95%CI=1.005～3.560,P=0.048)、咯血(OR=1.941,95%CI=1.087～3.465,P=0.025)、MDR(OR=3.342,95%CI=2.398～7.862,P<0.001)是肺结核患者FQs耐药的独立危险因素;Logistic回归方程Logit(P)=-3.571+0.838×民族+0.638×治疗史+0.663×咯血+1.468×MDR,基于此构建风险Nomogram预测模型,AUC为0.796(95%CI=0.717～0.876),Bootstrap法验证平均绝对误差为 0.015,通过Hosmer-Lemeshow拟合优度检验,预测模型有较好的校准能力(χ2=3.426,P=0.489).结论 肺结核患者FQs耐药率较高,其他民族、复治、咯血、MDR是肺结核患者FQs耐药的独立危险因素,构建Nomogram预测模型对于肺结核患者FQs耐药具有较好的预测价值,能够为临床诊断耐药结核病及为RR/MDR-TB制订合理治疗方案提供新思路.
Abstract
Background Rifampicin-resistant/multidrug-resistant tuberculosis(RR/MDR-TB)is featured by challenges in the treatment,low cure rate,and high infectivity.Fluoroquinolones(FQs),as the core drugs for the treatment of RR/MDR-TB,have a severe trend of resistance.Analyzing influencing factors for FQs can help to increase the cure rate of RR/MDR-TB and to control the occurrence of the pre-extensive drug resistance(pre-XDR)and extensive drug resistance.Objective To analyze the drug resistance of FQs in hospitalized patients with pulmonary tuberculosis and the influencing factors,and to construct and validate a Nomogram prediction model for the risk factors of drug resistance of FQs.Methods A total of 583 patients with pulmonary tuberculosis who were hospitalized in Guiyang Public Health Clinical Center from January 2021 to February 2022 and tested for drug sensitivity were retrospectively selected as study subjects.They were divided into the initial treatment group(296 patients)and the retreatment group(287 patients)according to the history of previous treatment.Moreover,they were divided into the FQs-resistant group(63 patients)and FQs-sensitive group(520 patients)according to their FQs-resistance status.The distribution of total resistance to 13 antituberculosis drugs in 583 patients was analyzed,and the baseline characteristics of patients in the FQs-resistant group and FQs-sensitive group were compared.After screening the characteristic variables using least absolute shrinkage and selection operator(LASSO)regression model,multivariate Logistic regression was performed to analyze the independent risk factors for the resistance of FQs.A Nomogram prediction model was constructed,and its performance was validated by calculating the area under the curve(AUC)of receiver operating characteristic(ROC),and plotting the calibration curve.Results Among 583 patients,520 cases were sensitive to FQs and 63 cases were resistant(resistance rate of 10.81%).The resistance rate of FQs was secondary to the total resistance rate of first-line antituberculosis drugs,including the isoniazid(36.36%),rifampicin(32.76%),streptomycin(21.61%),and ethambutol(12.86%).The resistance rates of rifampicin,isoniazid,ethambutol,streptomycin,levofloxacin,moxifloxacin and rifampicin resistance(RR),multidrug resistance(MDR),and pre-XDR were significantly higher in patients of the retreatment group than those of the initial treatment group(P<0.05).The proportions of patients with other ethnic,retreatment,acquired immunodeficiency syndrome(AIDS),history of drug abuse,cavitation,hemoptysis,history of irregular anti-TB and MDR were significantly higher in the FQs-resistance group than those of the FQs-sensitive group(P<0.05).Through LASSO regression,six variables of ethnicity,treatment history,AIDS,drug abuse history,hemoptysis,and MDR were screened out as influencing factors.Multivariate Logistic regression analysis showed that other ethnic(OR=2.313,95%CI=1.153-4.640,P=0.018),retreatment(OR=1.892,95%CI=1.005-3.560,P=0.048),hemoptysis(OR=1.941,95%CI=1.087-3.465,P=0.025),and MDR(OR=3.342,95%CI=2.398-7.862,P<0.001)were the independent risk factors for FQs resistance in patients with pulmonary tuberculosis.Logistic regression equation Logit(P)=-3.571+0.838×ethnicity+0.638×treatment history+0.663×hemoptysis+1.468×MDR.Based on which a risk Nomogram prediction model was constructed with an AUC of 0.796(95%CI=0.717-0.876).The Bootstrap method validated the mean absolute error of 0.015,and the predictive model had good calibration ability by the Hosmer-Lemeshow goodness-of-fit test(χ2=3.426,P=0.489).Conclusion Our findings suggest a high resistant rate of FQs in patients with pulmonary tuberculosis.Other ethnic,retreatment,hemoptysis,and MDR are independent risk factors for FQs resistance in patients.The constructed Nomogram prediction model has a good predictive value for FQs resistance in patients with pulmonary tuberculosis.Our study offers new insights into the clinical diagnosis of drug-resistant tuberculosis and the development of rational treatment regimens for RR/MDR-TB.
基金项目
"十三五"国家重大新药创制项目(2017ZX09304009)
贵阳市科技计划项目(筑科合同[2018]1-47号)
国家科技期刊平台
NSTL
万方数据