CAJ | 학술논문

目的：建立多种细胞因子鉴别诊断结核性胸腔积液的Binary Logistic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Binary Logistic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-α＞VEGF＞IL-2；联合诊断时， CXCL-10、IFN-γ、IL-27及 IL-33进入 Binary Logistic 回归模型，回归方程为 P ＝1／1＋e－（－9.498＋0.030×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（χ2＝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。（中华检验医学杂志，2015，38：562-566）
목적：건립다충세포인자감별진단결핵성흉강적액적Binary Logistic회귀모형，병여결핵감염T세포반점시험（ T-SPOT.TB）비교기진단준학성，평고기진단개치。방법병례대조연구。수집2011년12월지2013년6월재천진해하의원주원적흉강적액환자147례，분위결핵성흉강적액조（결핵조）95례화악성흉강적액조（대조조）52례。이용액상심편기술대소유환자적흉강적액진행γ-간우소（ IFN-γ）、추화인자 CXCL10（ CXCL-10）、종류배사인자-α（ TNF-α）、혈관내피생장인자（VEGF）、백세포개소2（IL-2）、백세포개소16（IL-16）、백세포개소17（IL-17）、백세포개소27（IL-27）、백세포개소33（IL-33）측정，동시행결핵감염T세포검측（T-SPOT.TB）。응용Binary Logistic회귀분석화ROC곡선건립회귀모형병학정기개솔예측치P적최괄진단계점。결과각세포인자단독진단시AUC비교：CXCL-10＞IL-27＞IFN-γ＞IL-33＞IL-17＞IL-16＞TNF-α＞VEGF＞IL-2；연합진단시， CXCL-10、IFN-γ、IL-27급 IL-33진입 Binary Logistic 회귀모형，회귀방정위 P ＝1／1＋e－（－9.498＋0.030×CXCL-10＋0.012×IFN-γ＋0.002×IL-27＋0.234×IL-33），기AUC、민감도화특이도분별위0.995、96.84％화98.08％，균우우각단항진단지표；기AUC（0.995±0.003）현저고우T-SPOT.TB（0.921±0.023），차이구유통계학의의（Z＝3.235，P＜0.01），동시，량방법진단결과적차이무통계학의의（χ2＝0.0625， P＞0.05），진단일치성교호（Kappa＝0.795＞0.75）。결론본연구적고통량、고령민도화고중복성적액상심편기술검측평태，위림상결핵성흉강적액적과학준학진단、치료급예방제공료일충신적사로여방법。（중화검험의학잡지，2015，38：562-566）
Objective To establish a diagnostic model of multiple cytokines for differential diagnosis of tuberculous pleural 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 pleural 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.Pleural 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-( -16.851+0.390 ×IFN-γ+0.006 ×IL-27+0.020 ×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 significantly greater ( Z=3.235, P <0.01), but no significant difference was found when it comes to diagnostic results consistency (χ2 =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 repeatability with high throughput provided a novel insight and method in the clinical diagnosis , treatment and prevention for tuberculous pleural effusion scientifically and accurately.