昆山市未抗病毒治疗HIV感染者总淋巴细胞计数与CD4^+T淋巴细胞计数的相关性  

Correlation between total lymphocyte count and CD4^+ T cell count among non-antiretroviral therapy HIV-1 infected individuals in Kunshan

作　　者：陈权[1] 薛黎坚[1] 王文明[1] 田昌伟[1] 王华[1] 姚庆完[1] Chert Quan Xue Lijian Wang Wenming Tian Chanzvei Wang Hua Yao Qingwan.(Kunshan Municipal Center for Disease Control and Prevention, Kunshan, Jiangsu 215300, China)

机构地区：[1]昆山市疾病预防控制中心,江苏昆山215300

出　　处：《中国艾滋病性病》2017年第4期280-283,共4页Chinese Journal of Aids & STD

基　　金：昆山市社会发展科技专项(KS1546)~~

摘　　要：目的应用决策树模型(CART),纳入总淋巴细胞(TLC)计数、血红蛋白(HGB)等多个血常规指标,研究未抗病毒治疗HIV感染者TLC与CD4^+T淋巴细胞(简称CD4细胞)计数的相关性,并与受试者工作特征曲线(简称ROC曲线)常规分类方法比较。方法选取昆山市未抗病毒治疗HIV感染者297例,采集433份血样标本,检测血常规指标和CD4细胞计数。将血常规指标与CD4细胞计数进行相关性分析,以CD4细胞计数≤350个/uL、≤500个/uL为临界点,分别计算CART、常规ROC曲线分类方法的灵敏度、特异度、阳性预测值(PPV)、阴性预测值(NPV)和约登指数。结果 TLC、HGB、白细胞(WBC)计数、红细胞(RBC)计数、血小板(PLT)计数、中性粒细胞(WLCC)计数与CD4细胞计数均显著相关(P<0.05),纳入TLC、HGB、RBC、WBC指标,CART模型分类CD4细胞计数≤350个/uL的灵敏度、特异度、PPV、NPV和约登指数分别为36.4%、95.3%、84.2%、68.6%和0.317;纳入TLC、HGB、RBC指标,CART模型分类CD4细胞计数≤500个/uL的灵敏度、特异度、PPV、NPV和约登指数分别为92.0%、40.9%、78.0%、69.2%和0.329;两个CART模型均略优于ROC曲线分类方法。结论应用CART模型纳入TLC、HGB等多个血常规指标能有效预测CD4细胞计数,可在资源有限地区用于未治疗HIV感染者疾病进展监测。Objective To explore the relationship between TLC and CD4^＋ T cell count among non-antiretroviral therapy HIV-1 infected patients, and compare the results with those from traditional ROC method by using decision tree algorithm （CART） based on total lymphocyte count （TLC）, hemoglobin （HGB） and other routine blood indexes. Methods A prospective study was conducted with 43a blood samples collected from 297 HIV-1 positive indi- viduals without receiving anti-retroviral therapy. TLC and other correlated routine blood cell count indexes were used to develop CART models based on CD4^＋ T cell count 4350 cells/μL, and 4500 cells/μL respectively. Sensitivity, specificity, PPV （positive predictive value）, NPV （negative predictive value）, Youden index were calculated and compared with those from ROC method. Results CD4^＋ T cell count was significantly associated with TLC, HGB, white blood cell count（WBC）, red blood cell count（RBC）, blood platelet cell count（PLT）, and neutrophil ceil count（WLCC）. The sensitivity, specificity, PPV, NPV and Youden index from CART Model for CD4^＋ T count 4350 cells/μL were 36.4%, 95.3%, 84.2%, 68.6% and 0. 317 respectively, and for CD4^＋ T count≤500 cells/μL L were 92.0%, 40.9%, 78.0%, 69.2% and 0. 329 respectively. CART models appeared superior to traditional ROC method. Conclusion The study shows that CART model can effectively predict CD4^＋ T cell count with reference to TLC, HGB and other routine blood indexes. CART model can be applied as a useful tool for CD4 ^＋ T count prediction in non-antiretroviral therapy HIV 1 positivesubjects in resource limited settings,

关 键 词：艾滋病 CD4+T淋巴细胞计数 决策树模型 总淋巴细胞计数 抗病毒治疗 

分 类 号：R512.91[医药卫生—内科学] R373.9[医药卫生—临床医学]