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肺结核患者治疗2个月后炎症生物标志物对治疗结果的预测:初步结果

Prediction of Treatment Outcome with Inflammatory Biomarkers after 2 Months of Therapy in Pulmonary Tuberculosis Patients: Preliminary Results.

作者信息

Stefanescu Simona, Cocoș Relu, Turcu-Stiolica Adina, Shelby Elena-Silvia, Matei Marius, Subtirelu Mihaela-Simona, Meca Andreea-Daniela, Stanciulescu Elena Camelia, Popescu Stefana Oana, Biciusca Viorel, Pisoschi Catalina-Gabriela

机构信息

Clinical Analysis Laboratory, Clinical Emergency County Hospital Craiova, 200642 Craiova, Romania.

Department of Medical Genetics, University of Medicine and Pharmacy "Carol Davila", 020032 Bucharest, Romania.

出版信息

Pathogens. 2021 Jun 22;10(7):789. doi: 10.3390/pathogens10070789.

Abstract

Pro-inflammatory mediators play an important role in the pathogenesis of pulmonary tuberculosis. Consecutively, 26 pulmonary tuberculosis patients were enrolled in our study based on the exclusion criteria. We have used Spearman's correlation analysis, hierarchical clustering and regression modelling to evaluate the association of 11 biomarkers with culture status after antituberculosis treatment. The results of our study demonstrated that six inflammatory biomarkers of 11, C-reactive protein (CRP), white blood cells (WBC), neutrophils, interferon gamma inducible protein 10, C-reactive protein (CRP) to albumin ratio (CAR) and neutrophil to albumin ratio (NAR), were significantly associated with culture negativity. The predictive ability of a composite model of seven biomarkers was superior to that of any single biomarker based on area under the receiver operating characteristic curve (AUC) analysis, indicating an excellent prediction efficacy (AUC:0.892; 95% CI:0.732-1.0). We also found that the highest significant trends and lower levels of CRP and IP-10 were observed in the two-month treated tuberculosis (TB) patients. We believe that our study may be valuable in providing preliminary results for an additional strategy in monitoring and management of the clinical outcome of pulmonary tuberculosis. Using a panel of predictors added a superior value in predicting culture status after anti-TB therapy.

摘要

促炎介质在肺结核发病机制中起重要作用。随后,根据排除标准,26例肺结核患者被纳入我们的研究。我们使用Spearman相关性分析、层次聚类和回归模型来评估11种生物标志物与抗结核治疗后培养状态的关联。我们的研究结果表明,11种炎症生物标志物中的6种,即C反应蛋白(CRP)、白细胞(WBC)、中性粒细胞、干扰素γ诱导蛋白10、C反应蛋白(CRP)与白蛋白比值(CAR)和中性粒细胞与白蛋白比值(NAR),与培养阴性显著相关。基于受试者工作特征曲线下面积(AUC)分析,七种生物标志物的复合模型的预测能力优于任何单一生物标志物,表明具有出色的预测效果(AUC:0.892;95%CI:0.732 - 1.0)。我们还发现,在治疗两个月的结核病(TB)患者中观察到CRP和IP - 10的最高显著趋势和较低水平。我们认为,我们的研究可能为监测和管理肺结核临床结局的额外策略提供初步结果。使用一组预测指标在预测抗结核治疗后的培养状态方面具有更高的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e4d/8308673/32ede660cb95/pathogens-10-00789-g001.jpg

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