摘要
目的建立多种细胞因子鉴别诊断结核性胸腔积液的BinaryLogistic回归模型，并与结核感染T细胞斑点试验（T—SPOT．TB）比较其诊断准确性，评估其诊断价值。方法病例对照研究。收集2011年12月至2013年6月在天津海河医院住院的胸腔积液患者147例，分为结核性胸腔积液组（结核组）95例和恶性胸腔积液组（对照组）52例。利用液相芯片技术对所有患者的胸腔积液进行γ-干扰素（IFN-γ）、趋化因子CXCL10（CXCL-10）、肿瘤坏死因子-α（TNF-α）、血管内皮生长因子（VEGF）、白细胞介素2（IL-2）、白细胞介素16（IL-16）、白细胞介素17（IL-17）、白细胞介素27（IL-27）、白细胞介素33（IL-33）测定，同时行结核感染T细胞检测（T-SPOT．TB）。应用BinaryLogistic回归分析和ROC曲线建立回归模型并确定其概率预测值P的最适诊断界点。结果各细胞因子单独诊断时AUC比较：CXCL-10〉IL-27〉IFN-γ〉IL-33〉IL-17〉IL-16〉TNF-d〉VEGF〉IL-2；联合诊断时，CXCL-10、IFN-γ、IL-27及IL-33进入BinaryLogistic回归模型，回归方程为P=1／1＋e-（-9.498＋0.30＋CXCL-10＋0.012×IFN-γ＋0.002×IL-27＋0.234×IL-33）,其AUC、敏感度和特异度分别为0．995、96．84％和98．08％，均优于各单项诊断指标；其AUC（0．995±0．003）显著高于T—SPOT．TB（0．921±0．023），差异具有统计学意义（Z=3．235，P〈0．01），同时，两方法诊断结果的差异无统计学意义（X2=0．0625，P〉0．05），诊断一致性较好（Kappa=0．795〉0．75）。结论本研究的高通量、高灵敏度和高重复性的液相芯片技术检测平台，为临床结核性胸腔积液的科学准确诊断、治疗及预防提供了一种新的思路与方法。
Objective To establish a diagnostic model of multiple cytokines for differential diagnosis of tuberculous pleura] effusion, and compare its diagnostic accuracy with tuberculosis infected T cells detection （T-SPOT. TB ） in order to evaluate its diagnostic performance. Methods Case-control study. Totally 147 patients with pleura] fluid in Tianjin Haihe Hospital were enrolled and categorized as tuberculous pleural effusion group （ n = 95 ） and malignant pleural effusion group （ n = 52 ） from December 2011 to June 2013. Pleura] effusion cytokines including interferon-γ （IFN-γ）, C-X-C motif chemokine 10 （ CXCL-10 ）, tumor necrosis factor-α （ TNF-α）, vascular endothelial growth factor （ VEGF）, IL-2, IL-16, IL-17, IL-27 and IL-33 were tested by liquid chip technology and analyzed by Binary Logistic regression and receiver operating characteristic curve （ROC） , and the pleural effusion was also detected by tuberculosis infected T cells detection （ T-SPOT. TB） as a control. Results The comparison of the AUC of cytokines is ： CXCL-10 〉 IL-27 〉 IFN-γ〉 IL-33 〉 IL-17 〉 IL-16 〉 TNF-α 〉 VEGF 〉 IL-2; After that, CXCL-10, IFN-γ, IL-27 and IL-33 were included the Binary Logistic regression model. The regression equation is P=1/1＋e-（-9.498＋0.30＋CXCL-10＋0.012×IFN-γ＋0.002×IL-27＋0.234×IL-33）The AUC, sensitivity and specificity of the diagnostic model were 99. 5%, 96. 84%, and 98.08%, respectively. Both AUC and sensitivity of the diagnostic model were superior to those of any single index. Compared with T-SPOT. TB （0. 995 ± 0. 003 ）, the AUC of the diagnostic model （0. 921 ± 0. 023 ） was signifieantly greater （ Z = 3. 235, P 〈 0. 01 ）, but no signifieant differenee was found when it comes to diagnostic results consistency（ X2 =0. 062 5, P 〉 0.05 ）. The Kappa of the two methods was 0. 795, which meant fine agreement of the evaluations of the two raters. Conclusion The application of liquid array technology of high sensitivity and repea
出处
《中华检验医学杂志》
CAS
CSCD
北大核心
2015年第8期562-566,共5页
Chinese Journal of Laboratory Medicine
基金
天津市卫生局科技基金（2013KZ042）
