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Article(id=1311350398124909281, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202601451, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1769270400000, receivedDateStr=2026-01-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579898625, onlineDateStr=2026-09-28, pubDate=1786291200000, pubDateStr=2026-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579898625, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579898625, creator=13701087609, updateTime=1790579898625, updator=13701087609, issue=Issue{id=1311350193946194882, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='15', pageStart='2689', pageEnd='2880', issueExtLink='null', onlineDate='null', pubDate='1786291200000', pubDateStr='2026-08-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790579849945, creator='13701087609', updateTime=1790588319569, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311385718195315029, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311385718195315030, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2720, endPage=2725, ext={EN=ArticleExt(id=1311350399987180258, articleId=1311350398124909281, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Factors influencing the CD4/CD8 ratio trajectory and its association with mortality in HIV-infected patients, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the dynamic trajectory of the CD4/CD8 ratio and its influencing factors in human immunodeficiency virus (HIV)-infected patients after initiating antiretroviral therapy (ART), and to explore its association with risk of mortality.

Methods

Data were obtained from HIV-infected patients who initiated ART between 2005 and 2023 in Wuxi.A latent class trajectory model was adopted to identify distinct trajectories of CD4/CD8 ratio. A multivariable logistic regression model was applied to analyze the factors influencing the trajectories of CD4/CD8 ratio, while a generalized linear mixed model tree (GLMMT) was employed to explore population characteristics associated with trajectory group membership. Furthermore,the Cox proportional hazards regression model was used to assess the association between trajectories and mortality.

Results

A total of 3 808 HIV-infected patients were included. Two distinct trajectories of CD4/CD8 ratio were identified: a gradual recovery group(28.02%, 1 067/3 808) and a sustained inversion group(71.98%, 2 741/3 808). Multivariable logistic regression analysis revealed that patients who were male(OR=1.29, 95% CI: 1.01-1.64), infected through homosexual contact (OR=1.25,95% CI: 1.04-1.49), initiated ART more than 30 days after diagnosis (OR=1.70, 95% CI: 1.47-1.97), had baseline CD4 count <200 cells/μl (OR=1.21, 95% CI: 1.03-1.43), and had baseline CD4/CD8 ratio <1 (OR=2.24, 95% CI: 1.59-3.17) were more likely to belong to the sustained inversion group. GLMMT analysis showed that the prevalence of sustained CD4/CD8 ratio inversion was 77.72% (1 427/1 836) among HIV-infected individuals with ART initiation >30 days and a baseline CD4/CD8 ratio <1, and 73.85% (401/543) among those with ART initiation ≤30 days who were male and had a baseline CD4 count <200 cells/μl. Furthermore, individuals in the sustained inversion group had a significantly increased risk of acquired immunodeficiency syndrome (AIDS)-related death (HR=4.90, 95% CI: 1.52-15.83), but no significant association was found with non-AIDS-related death.

Conclusion

The persistent inversion of the CD4/CD8 ratio is common among people living with HIV. A comprehensive assessment of immune status and disease progression should, therefore, include not only the CD4 count but also the CD4/CD8 ratio, while fully considering the influence of demographic and behavioral factors.

, authors=Bo-lin YANG, Ji-biao CHEN, Han-lu YIN, Jing GU, Zhu-ping XU, Xiao-jun MENG, authorsList=Bo-lin YANG, Ji-biao CHEN, Han-lu YIN, Jing GU, Zhu-ping XU, Xiao-jun MENG, authorCompany=null, correspAuthors=Xiao-jun MENG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311350401002201831, articleId=1311350398124909281, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=HIV感染者CD4/CD8比值变化轨迹的影响因素及其与死亡风险的关联研究, columnId=1228016567632462653, journalTitle=现代预防医学, columnName=流行病与统计方法, runingTitle=null, highlight=null, articleAbstract=
目的

分析人类免疫缺陷病毒（human immunodeficiency virus，HIV）感染者启动抗逆转录病毒治疗（antiretroviral therapy，ART）后CD4/CD8比值的动态变化轨迹及影响因素，并探索其与死亡风险的关联。

方法

收集2005—2023年无锡市启动ART的HIV感染者监测数据，采用潜在类别轨迹模型识别CD4/CD8比值变化轨迹，使用多因素logistic回归模型分析其影响因素，运用广义线性混合模型树(generalized linear mixed model tree, GLMMT)探索识别影响轨迹组别归属的人群特征，采用Cox比例风险回归模型分析轨迹与死亡的关联。

结果

共纳入3 808例HIV感染者，识别出两类CD4/CD8比值变化轨迹，分别为逐步恢复组（28.02%，1 067/3 808）和持续倒置组（71.98%，2 741/3 808）。多因素logistic回归分析显示，男性（OR=1.29, 95%CI: 1.01～1.64）、经同性传播（OR=1.25, 95%CI: 1.04～1.49）、启动ART时间>30 d（OR=1.70, 95%CI: 1.47～1.97）、基线CD4计数水平<200 个/μl （OR=1.21, 95%CI: 1.03～1.43）、基线CD4/CD8比值水平<1（OR=2.24, 95%CI: 1.59～3.17）的感染者的CD4/CD8比值变化轨迹更可能为持续倒置组。GLMMT分析结果显示，ART启动时间>30 d、基线CD4/CD8比值<1的HIV感染者CD4/CD8比值持续倒置比例为77.72%（1 427/1 836）；ART启动时间≤30 d、男性、基线CD4计数<200个/μl者持续倒置比例为73.85%（401/543）。CD4/CD8比值持续倒置组发生获得性免疫缺陷综合征（acquired immunodeficiency syndrome,AIDS）相关死亡的风险更高（HR=4.90, 95%CI: 1.52～15.83），但与非AIDS相关死亡无统计学关联。

结论

HIV感染者的CD4/CD8比值持续倒置现象较为普遍。在评估免疫状态和疾病进展时，除CD4计数外，还应关注CD4/CD8比值，并充分考虑人口学及行为学因素的影响。

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杨柏林（1994—），女，硕士，主管医师，研究方向：传染病流行病学

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孟晓军，E-mail:
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杨柏林（1994—），女，硕士，主管医师，研究方向：传染病流行病学

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CD4/CD8 ratio and CD8+T -cell count as prognostic markers for non-AIDS mortality in People living with HIV.A systematic review and meta-analysis[J].Frontiers in Immunology, 2024, 15: 1343124., articleTitle=CD4/CD8 ratio and CD8+T -cell count as prognostic markers for non-AIDS mortality in People living with HIV.A systematic review and meta-analysis, refAbstract=null), Reference(id=1311350415636128568, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, doi=null, pmid=null, pmcid=null, year=2022, volume=80, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[24], rfOrder=25, authorNames=Serrano-Villar S, Wu KL, Hunt PW, journalName=EBioMedicine, refType=null, unstructuredReference=Serrano-Villar S, Wu KL, Hunt PW, et al. Predictive value of CD8+ T cell and CD4/CD8 ratio at two years of successful ART in the risk of AIDS and non-AIDS events[J]. EBioMedicine, 2022, 80:104072., articleTitle=Predictive value of CD8+ T cell and CD4/CD8 ratio at two years of successful ART in the risk of AIDS and non-AIDS events, refAbstract=null)], funds=[Fund(id=1311350406568043293, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, awardId=JSJK2026M00006, language=CN, fundingSource=江苏省疾病预防控制局项目(JSJK2026M00006), fundOrder=null, country=null), Fund(id=1311350410049315614, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, awardId=BJ2023097; FZXK2021010, language=CN, fundingSource=无锡市卫生健康委项目(BJ2023097; FZXK2021010), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1311350401358717672, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, xref=null, ext=[AuthorCompanyExt(id=1311350401367106281, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, companyId=1311350401358717672, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi, Jiangsu 214023, China), AuthorCompanyExt(id=1311350401388077802, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, companyId=1311350401358717672, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=无锡市疾病预防控制中心（南京医科大学附属无锡疾病预防控制中心），江苏 无锡 214023)])], figs=[ArticleFig(id=1311350405481718545, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=EN, label=Figure 1, caption=Trajectory of the CD4/CD8 ratio in HIV-infected individuals, figureFileSmall=pfBFB7rYq5wHt6MENz5TRA==, figureFileBig=FiaTi1vX0E6wQV+u3pi5hA==, tableContent=null), ArticleFig(id=1311350405548827410, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=CN, label=图1, caption=HIV感染者CD4/CD8比值的变化轨迹, figureFileSmall=pfBFB7rYq5wHt6MENz5TRA==, figureFileBig=FiaTi1vX0E6wQV+u3pi5hA==, tableContent=null), ArticleFig(id=1311350405733376787, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=EN, label=Figure 2, caption=Exploratory identification of the trajectory group of CD4/CD8 ratio using GLMMT, figureFileSmall=eH6LYd26w3j0z2aMlA6U/g==, figureFileBig=G0XUN3vN35+TMGs5KUVEHA==, tableContent=null), ArticleFig(id=1311350405808874260, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=CN, label=图2, caption=探索性识别CD4/CD8比值变化轨迹组的GLMMT

注：灰色和黑色分别表示逐步恢复组和持续倒置组。

, figureFileSmall=eH6LYd26w3j0z2aMlA6U/g==, figureFileBig=G0XUN3vN35+TMGs5KUVEHA==, tableContent=null), ArticleFig(id=1311350405930509077, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=EN, label=Table 1, caption=

Variable assignment table

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称编码
CD4/CD8比值变化轨迹0=逐步恢复组，1=持续倒置组
性别0=女，1=男
确诊HIV年龄（岁）0=<50，1=≥50
学历0=高中及以下，1=高中以上
婚姻状况0=非在婚，1=在婚
传播途径0=非同性传播，1=同性传播
基线治疗方案0=其他，1=TDF/AZT+3TC+EFV/NVP
启动ART时间（d）0=≤30，1=>30
基线CD4计数水平（个/μl）0=≥200，1=<200
基线CD4/CD8比值水平0=≥1，1=<1
), ArticleFig(id=1311350405993423638, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=CN, label=表1, caption=

变量赋值表

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称编码
CD4/CD8比值变化轨迹0=逐步恢复组，1=持续倒置组
性别0=女，1=男
确诊HIV年龄（岁）0=<50，1=≥50
学历0=高中及以下，1=高中以上
婚姻状况0=非在婚，1=在婚
传播途径0=非同性传播，1=同性传播
基线治疗方案0=其他，1=TDF/AZT+3TC+EFV/NVP
启动ART时间（d）0=≤30，1=>30
基线CD4计数水平（个/μl）0=≥200，1=<200
基线CD4/CD8比值水平0=≥1，1=<1
), ArticleFig(id=1311350406064726807, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=EN, label=Table 2, caption=

Evaluation of the adequacy of the latent class trajectory model

, figureFileSmall=null, figureFileBig=null, tableContent=
Class BIC平均后验概率每个类别的人数占比 (%)
class1class2class3class4class5class1class2class3class4class5
1-30 372.251.00100.00
2-32 243.740.820.8828.0271.98
3-33 074.410.890.910.813.1577.7819.07
4-33 753.960.890.870.800.762.8972.745.2319.14
5-33 921.620.640.790.900.800.7410.0164.002.764.7518.49
), ArticleFig(id=1311350406136029976, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=CN, label=表2, caption=

LCTM的充分性评估

, figureFileSmall=null, figureFileBig=null, tableContent=
Class BIC平均后验概率每个类别的人数占比 (%)
class1class2class3class4class5class1class2class3class4class5
1-30 372.251.00100.00
2-32 243.740.820.8828.0271.98
3-33 074.410.890.910.813.1577.7819.07
4-33 753.960.890.870.800.762.8972.745.2319.14
5-33 921.620.640.790.900.800.7410.0164.002.764.7518.49
), ArticleFig(id=1311350406215721753, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=EN, label=Table 3, caption=

Analysis of influencing factors on the trajectory of CD4/CD8 ratio in HIV-infected individuals ［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量逐步恢复组
(n=1 067)		持续倒置组
(n=2 741)		单因素分析多因素分析
OR (95%CI)P值aOR (95%CI)P值
性别
女167 (37.11)283 (62.89)1.001.00
男900 (26.80)2 458 (73.20)1.61 (1.31～1.98)< 0.0011.29 (1.01～1.64)0.040
确诊HIV年龄（岁）
< 50723 (26.56)1 999 (73.44)1.001.00
≥ 50344 (31.68)742 (68.32)0.78 (0.67～0.91)0.0020.91 (0.76～1.09)0.308
学历
高中及以下515 (30.06)1 198 (69.94)1.001.00
高中以上552 (26.35)1 543 (73.65)1.20 (1.04～1.38)0.0111.04 (0.88～1.22)0.656
婚姻状态
非在婚644 (27.43)1 704 (72.57)1.00
在婚423 (28.97)1 037 (71.03)0.93 (0.80～1.07)0.302
传播途径
非同性传播445 (32.15)939 (67.85)1.001.00
同性传播622 (25.66)1 802 (74.34)1.37 (1.19～1.59)< 0.0011.25 (1.04～1.49)0.014
基线治疗方案
其他296 (26.98)801 (73.02)1.00
TDF/AZT+3TC+EFV/NVP771 (28.44)1 940 (71.56)0.93 (0.79～1.09)0.365
启动ART时间（d）
≤ 30621 (33.01)1 260 (66.99)1.001.00
> 30446 (23.14)1 481 (76.86)1.64 (1.42～1.89)< 0.0011.70 (1.47～1.97)< 0.001
基线CD4计数水平（个/μl）
≥ 200778 (28.81)1 922 (71.19)1.001.00
< 200289 (26.08)819 (73.92)1.15 (0.98～1.34)0.0881.21 (1.03～1.43)0.020
基线CD4/CD8比值水平
≥ 166 (46.15)77 (53.85)1.001.00
< 11 001 (27.31)2 664 (72.69)2.28 (1.63～3.19)< 0.0012.24 (1.59～3.17)< 0.001
), ArticleFig(id=1311350406312190746, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=CN, label=表3, caption=

HIV感染者CD4/CD8比值变化轨迹的影响因素分析［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量逐步恢复组
(n=1 067)		持续倒置组
(n=2 741)		单因素分析多因素分析
OR (95%CI)P值aOR (95%CI)P值
性别
女167 (37.11)283 (62.89)1.001.00
男900 (26.80)2 458 (73.20)1.61 (1.31～1.98)< 0.0011.29 (1.01～1.64)0.040
确诊HIV年龄（岁）
< 50723 (26.56)1 999 (73.44)1.001.00
≥ 50344 (31.68)742 (68.32)0.78 (0.67～0.91)0.0020.91 (0.76～1.09)0.308
学历
高中及以下515 (30.06)1 198 (69.94)1.001.00
高中以上552 (26.35)1 543 (73.65)1.20 (1.04～1.38)0.0111.04 (0.88～1.22)0.656
婚姻状态
非在婚644 (27.43)1 704 (72.57)1.00
在婚423 (28.97)1 037 (71.03)0.93 (0.80～1.07)0.302
传播途径
非同性传播445 (32.15)939 (67.85)1.001.00
同性传播622 (25.66)1 802 (74.34)1.37 (1.19～1.59)< 0.0011.25 (1.04～1.49)0.014
基线治疗方案
其他296 (26.98)801 (73.02)1.00
TDF/AZT+3TC+EFV/NVP771 (28.44)1 940 (71.56)0.93 (0.79～1.09)0.365
启动ART时间（d）
≤ 30621 (33.01)1 260 (66.99)1.001.00
> 30446 (23.14)1 481 (76.86)1.64 (1.42～1.89)< 0.0011.70 (1.47～1.97)< 0.001
基线CD4计数水平（个/μl）
≥ 200778 (28.81)1 922 (71.19)1.001.00
< 200289 (26.08)819 (73.92)1.15 (0.98～1.34)0.0881.21 (1.03～1.43)0.020
基线CD4/CD8比值水平
≥ 166 (46.15)77 (53.85)1.001.00
< 11 001 (27.31)2 664 (72.69)2.28 (1.63～3.19)< 0.0012.24 (1.59～3.17)< 0.001
), ArticleFig(id=1311350406391882523, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=EN, label=Table 4, caption=

Analysis of the correlation between the trajectory of CD4/CD8 ratio and mortality

, figureFileSmall=null, figureFileBig=null, tableContent=
变量死亡人数/总人数模型1模型2模型3
HR(95% CI)P值HR(95% CI)P值HR(95% CI)P值
AIDS相关死亡
逐步恢复组3/1 0671.001.001.00
持续倒置组45/2 7414.66 (1.45～15.02)0.0107.99 (1.55～16.06)0.0074.90 (1.52～15.83)0.008
非AIDS相关死亡
逐步恢复组23/1 0671.001.001.00
持续倒置组71/2 7410.96 (0.60～1.54)0.8770.98 (0.61～1.57)0.9271.08 (0.67～1.74)0.749
确诊HIV年龄≥50岁*
AIDS相关死亡
逐步恢复组1/3441.001.001.00
持续倒置组20/7427.65 (1.03～57.00)0.0476.96 (0.93～52.24)0.0596.97 (0.92～53.03)0.061
非AIDS相关死亡
逐步恢复组15/3441.001.001.00
持续倒置组52/7421.37 (0.77～2.44)0.2791.28 (0.72～2.29)0.4021.27 (0.71～2.29)0.423
确诊HIV年龄<50岁*
AIDS相关死亡
逐步恢复组2/7231.001.001.00
持续倒置组25/1 9993.64 (0.86～15.37)0.0794.39 (1.04～18.60)0.0444.27 (1.01～18.13)0.049
非AIDS相关死亡
逐步恢复组8/7231.001.001.00
持续倒置组19/1 9990.68 (0.30～1.56)0.3640.66 (0.29～1.52)0.3300.70 (0.30～1.60)0.395
), ArticleFig(id=1311350406467379996, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350398124909281, language=CN, label=表4, caption=

CD4/CD8比值变化轨迹与死亡的关联性分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量死亡人数/总人数模型1模型2模型3
HR(95% CI)P值HR(95% CI)P值HR(95% CI)P值
AIDS相关死亡
逐步恢复组3/1 0671.001.001.00
持续倒置组45/2 7414.66 (1.45～15.02)0.0107.99 (1.55～16.06)0.0074.90 (1.52～15.83)0.008
非AIDS相关死亡
逐步恢复组23/1 0671.001.001.00
持续倒置组71/2 7410.96 (0.60～1.54)0.8770.98 (0.61～1.57)0.9271.08 (0.67～1.74)0.749
确诊HIV年龄≥50岁*
AIDS相关死亡
逐步恢复组1/3441.001.001.00
持续倒置组20/7427.65 (1.03～57.00)0.0476.96 (0.93～52.24)0.0596.97 (0.92～53.03)0.061
非AIDS相关死亡
逐步恢复组15/3441.001.001.00
持续倒置组52/7421.37 (0.77～2.44)0.2791.28 (0.72～2.29)0.4021.27 (0.71～2.29)0.423
确诊HIV年龄<50岁*
AIDS相关死亡
逐步恢复组2/7231.001.001.00
持续倒置组25/1 9993.64 (0.86～15.37)0.0794.39 (1.04～18.60)0.0444.27 (1.01～18.13)0.049
非AIDS相关死亡
逐步恢复组8/7231.001.001.00
持续倒置组19/1 9990.68 (0.30～1.56)0.3640.66 (0.29～1.52)0.3300.70 (0.30～1.60)0.395
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HIV感染者CD4/CD8比值变化轨迹的影响因素及其与死亡风险的关联研究
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杨柏林 , 陈积标 , 尹寒露 , 顾静 , 许祝平 , 孟晓军
现代预防医学 | 流行病与统计方法 2026,53(15): 2720-2725
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现代预防医学 |流行病与统计方法 2026 , 53 (15) : 2720 -2725
HIV感染者CD4/CD8比值变化轨迹的影响因素及其与死亡风险的关联研究
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杨柏林, 陈积标, 尹寒露, 顾静, 许祝平, 孟晓军
作者信息
  • 无锡市疾病预防控制中心（南京医科大学附属无锡疾病预防控制中心），江苏 无锡 214023
通讯作者:
孟晓军，E-mail:
作者简介:

杨柏林（1994—），女，硕士，主管医师，研究方向：传染病流行病学

Factors influencing the CD4/CD8 ratio trajectory and its association with mortality in HIV-infected patients
Bo-lin YANG, Ji-biao CHEN, Han-lu YIN, Jing GU, Zhu-ping XU, Xiao-jun MENG
Affiliations
  • The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi, Jiangsu 214023, China
出版时间: 2026-08-10 doi: 10.20043/j.cnki.MPM.202601451
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摘要
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目的

分析人类免疫缺陷病毒（human immunodeficiency virus，HIV）感染者启动抗逆转录病毒治疗（antiretroviral therapy，ART）后CD4/CD8比值的动态变化轨迹及影响因素，并探索其与死亡风险的关联。

方法

收集2005—2023年无锡市启动ART的HIV感染者监测数据，采用潜在类别轨迹模型识别CD4/CD8比值变化轨迹，使用多因素logistic回归模型分析其影响因素，运用广义线性混合模型树(generalized linear mixed model tree, GLMMT)探索识别影响轨迹组别归属的人群特征，采用Cox比例风险回归模型分析轨迹与死亡的关联。

结果

共纳入3 808例HIV感染者，识别出两类CD4/CD8比值变化轨迹，分别为逐步恢复组（28.02%，1 067/3 808）和持续倒置组（71.98%，2 741/3 808）。多因素logistic回归分析显示，男性（OR=1.29, 95%CI: 1.01～1.64）、经同性传播（OR=1.25, 95%CI: 1.04～1.49）、启动ART时间>30 d（OR=1.70, 95%CI: 1.47～1.97）、基线CD4计数水平<200 个/μl （OR=1.21, 95%CI: 1.03～1.43）、基线CD4/CD8比值水平<1（OR=2.24, 95%CI: 1.59～3.17）的感染者的CD4/CD8比值变化轨迹更可能为持续倒置组。GLMMT分析结果显示，ART启动时间>30 d、基线CD4/CD8比值<1的HIV感染者CD4/CD8比值持续倒置比例为77.72%（1 427/1 836）；ART启动时间≤30 d、男性、基线CD4计数<200个/μl者持续倒置比例为73.85%（401/543）。CD4/CD8比值持续倒置组发生获得性免疫缺陷综合征（acquired immunodeficiency syndrome,AIDS）相关死亡的风险更高（HR=4.90, 95%CI: 1.52～15.83），但与非AIDS相关死亡无统计学关联。

结论

HIV感染者的CD4/CD8比值持续倒置现象较为普遍。在评估免疫状态和疾病进展时，除CD4计数外，还应关注CD4/CD8比值，并充分考虑人口学及行为学因素的影响。

HIV感染者  /  CD4/CD8比值  /  轨迹  /  AIDS相关死亡
Objective

To analyze the dynamic trajectory of the CD4/CD8 ratio and its influencing factors in human immunodeficiency virus (HIV)-infected patients after initiating antiretroviral therapy (ART), and to explore its association with risk of mortality.

Methods

Data were obtained from HIV-infected patients who initiated ART between 2005 and 2023 in Wuxi.A latent class trajectory model was adopted to identify distinct trajectories of CD4/CD8 ratio. A multivariable logistic regression model was applied to analyze the factors influencing the trajectories of CD4/CD8 ratio, while a generalized linear mixed model tree (GLMMT) was employed to explore population characteristics associated with trajectory group membership. Furthermore,the Cox proportional hazards regression model was used to assess the association between trajectories and mortality.

Results

A total of 3 808 HIV-infected patients were included. Two distinct trajectories of CD4/CD8 ratio were identified: a gradual recovery group(28.02%, 1 067/3 808) and a sustained inversion group(71.98%, 2 741/3 808). Multivariable logistic regression analysis revealed that patients who were male(OR=1.29, 95% CI: 1.01-1.64), infected through homosexual contact (OR=1.25,95% CI: 1.04-1.49), initiated ART more than 30 days after diagnosis (OR=1.70, 95% CI: 1.47-1.97), had baseline CD4 count <200 cells/μl (OR=1.21, 95% CI: 1.03-1.43), and had baseline CD4/CD8 ratio <1 (OR=2.24, 95% CI: 1.59-3.17) were more likely to belong to the sustained inversion group. GLMMT analysis showed that the prevalence of sustained CD4/CD8 ratio inversion was 77.72% (1 427/1 836) among HIV-infected individuals with ART initiation >30 days and a baseline CD4/CD8 ratio <1, and 73.85% (401/543) among those with ART initiation ≤30 days who were male and had a baseline CD4 count <200 cells/μl. Furthermore, individuals in the sustained inversion group had a significantly increased risk of acquired immunodeficiency syndrome (AIDS)-related death (HR=4.90, 95% CI: 1.52-15.83), but no significant association was found with non-AIDS-related death.

Conclusion

The persistent inversion of the CD4/CD8 ratio is common among people living with HIV. A comprehensive assessment of immune status and disease progression should, therefore, include not only the CD4 count but also the CD4/CD8 ratio, while fully considering the influence of demographic and behavioral factors.

HIV-infected patients  /  CD4/CD8 ratio  /  Trajectory  /  AIDS-related death
杨柏林, 陈积标, 尹寒露, 顾静, 许祝平, 孟晓军. HIV感染者CD4/CD8比值变化轨迹的影响因素及其与死亡风险的关联研究. 现代预防医学, 2026 , 53 (15) : 2720 -2725 . DOI: 10.20043/j.cnki.MPM.202601451
Bo-lin YANG, Ji-biao CHEN, Han-lu YIN, Jing GU, Zhu-ping XU, Xiao-jun MENG. Factors influencing the CD4/CD8 ratio trajectory and its association with mortality in HIV-infected patients[J]. Modern Preventive Medicine, 2026 , 53 (15) : 2720 -2725 . DOI: 10.20043/j.cnki.MPM.202601451
正文
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随着抗逆转录病毒治疗（antiretroviral therapy，ART）的推广，人类免疫缺陷病毒(human immunodeficiency virus, HIV)感染者和获得性免疫缺陷综合征（acquired immunodeficiency syndrome，AIDS）病人的寿命得到了显著延长，但HIV感染者出现严重临床事件的风险和死亡率仍高于一般人群[1-2]。CD4+ T淋巴细胞（CD4）计数被普遍用来指导ART方案的选择和疗效评估，但CD4计数恢复正常并不意味着完全恢复正常的免疫功能[1]。研究表明，CD4/CD8比值与免疫衰老和炎症标志物相关，其动态变化能够提供CD4计数和病毒载量之外的额外信息，是监测HIV感染者免疫功能障碍的有效指标[1]。即使启动ART后，实现病毒抑制，CD4计数逐渐恢复，但由于CD8+ T淋巴细胞(CD8)计数下降缓慢，且常存在功能紊乱，大多数感染者的CD4/CD8比值难以恢复正常。在启动ART时基线CD4计数≤200个/μl的HIV感染者中，超过80%未实现CD4/CD8比值正常化[3]。持续的CD4/CD8比值倒置（即CD4/CD8比值<1.0）的HIV感染者往往伴随着T细胞活化、耗竭及免疫衰老相关生物标志物升高[4]，其发生心血管事件、非艾滋病定义的恶性肿瘤、全因死亡以及AIDS相关死亡的风险增加[1,5]。因此， CD4/CD8比值作为一个反映免疫重建质量与炎症状态的综合指标，对于评估HIV感染者的长期预后具有重要的临床意义。
既往研究评估了HIV感染者急性感染期、长期病毒抑制状态及不同人群的CD4/CD8比值动态变化轨迹[6-11]，并探讨了其与疾病进展的关联，但对不同轨迹类别的影响因素及其与死亡风险的关联仍缺乏深入探讨。为此，本研究利用无锡市HIV感染者CD4/CD8比值的长期动态监测数据进行分析，旨在识别CD4/CD8比值的动态变化轨迹，分析其影响因素及高风险人群特征，并探讨不同轨迹与死亡的关联，为HIV感染者的精准分层管理提供科学依据。
1　资料与方法
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1.1　研究对象
本研究数据来源于中国疾病预防控制信息系统中的艾滋病综合防治信息系统，纳入2005年1月1日—2023年12月31日无锡市启动ART的HIV感染者。通过系统内“现住址”字段筛选出所有登记为江苏省无锡市的HIV感染者，随访、死亡或失访数据提取截止时间为2024年12月31日。纳入标准：（1）基线记录完整；（2）年龄≥18岁；（3）现住址在无锡市，在无锡市接受定期随访治疗；（4）具有至少3次同时测量的CD4计数、CD8计数记录。排除标准：重复报告病例（同一感染者多次上报）或关键数据字段（如启动ART时间等）缺失的病例记录。本研究经无锡市疾病预防控制中心伦理委员会审查确认，符合免除伦理审查的条件。鉴于此研究为利用既往监测数据进行分析，伦理委员会豁免了对患者知情同意的要求。
1.2　研究方法
收集研究对象的一般人口学信息（性别、年龄、婚姻状况、文化程度等）、感染途径、基线治疗方案、启动ART时间（从确诊HIV感染到启动ART的时间）、定期CD4、CD8检测结果等。
1.3　死因分类
依据个案/治疗随访表中填写的死亡原因及死亡编码（CoDe）[12]，将病例死因分为AIDS相关死亡和非AIDS相关死亡。AIDS相关死亡是指病例死因为AIDS机会性感染、AIDS相关肿瘤、AIDS相关特指疾病和综合征等[13]。除AIDS相关死亡外，所有其他死亡均为非AIDS相关死亡。
1.4　统计学分析
使用Excel（Office 2019）软件建立数据库，使用R 4.3.3软件进行统计分析。对CD4/CD8比值进行平方根变换，转换后近似服从正态分布[14]。采用潜在类别轨迹模型（latent class trajectory model,LCTM）[15]识别CD4/CD8比值随时间的变化轨迹，拟合2～5组CD4/CD8比值变化轨迹[6]，基于最小贝叶斯信息准则（Bayesian information criterion,BIC）选择最佳轨迹数量，同时保持每个类别的平均后验概率超过70%，且每个类别的人数≥总体的5%。采用logistic回归模型探讨影响CD4/CD8比值变化轨迹的独立因素，将单因素logistic回归分析P<0.2的变量纳入多因素logistic回归模型。广义线性混合模型树（generalized linear mixed model tree,GLMMT）[16]是一种将基于模型的递归分割与广义线性效应混合模型相结合的机器学习方法，本研究运用此模型探索CD4/CD8比值变化轨迹组别归属的不同影响因素间的交互作用。GLMMT以CD4/CD8比值变化轨迹组别为响应变量，以HIV感染者编码为随机截距，以P= 0.05作为节点划分的显著性界值，采用迭代估计算法进行拟合，识别决定轨迹组别归属的关键因素。使用Cox比例风险回归模型探索CD4/CD8比值变化轨迹与AIDS相关死亡、非AIDS相关死亡之间的关系。所有分析均采用双侧检验，检验水准α= 0.05。变量编码情况见表1。
2　结果
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2.1　调查对象基本情况
本研究共纳入3 808例HIV感染者，其中88.18%为男性，年龄<50岁者占71.48%，同性传播占63.66%。 71.19%的人基线治疗方案为替诺福韦/齐多夫定+拉米夫定+依非韦伦/奈韦拉平（TDF/AZT+3TC+EFV/NVP），49.40%的人在确证HIV后30 d内启动ART，29.10%的人基线CD4计数<200 个/μl，96.24%的人基线CD4/CD8比值<1。
2.2　CD4/CD8比值变化轨迹
根据LCTM拟合最佳轨迹数量的选择准则，共识别出2条CD4/CD8比值的变化轨迹，分别为逐步恢复组和持续倒置组，见表2、图1。逐步恢复组（28.02%，1 067/3 808）中的CD4/CD8比值逐渐增长，并最终恢复至正常水平；而持续倒置组（71.98%，2 741/3 808）的CD4/CD8比值虽缓慢增长，但未恢复至正常水平，持续保持比例倒置。
2.3　CD4/CD8比值变化轨迹的影响因素
多因素logistic分析结果显示，男性、经同性传播、启动ART时间>30 d、基线CD4计数水平<200 个/μl、基线CD4/CD8比值<1的HIV感染者更可能为CD4/CD8比值持续倒置组。见表3。
GLMMT分析结果显示，研究对象被划分为7个亚组，其中，启动ART时间是最关键的分层变量。启动ART时间>30 d且基线CD4/CD8比值<1的HIV感染者CD4/CD8比值持续倒置比例高达77.72%（1 427/1 836，其中同性传播、异性传播及其他分别为79.84%、74.20%）；启动ART时间≤30 d、男性、基线CD4计数<200个/μl者持续倒置比例为73.85%（401/543）。见图2。
2.4　CD4/CD8比值变化轨迹与死亡的关联分析
共有48例发生AIDS相关死亡，CD4/CD8比值持续倒置组发生AIDS相关死亡的风险是逐步恢复组的4.90倍（HR=4.90, 95%CI: 1.52～15.83）。亚组分析显示，在确证HIV年龄<50岁的HIV感染者中，该风险为4.27倍（HR=4.27, 95%CI: 1.01～18.13）；但在确证HIV年龄≥50岁的感染者中，两组间AIDS相关死亡风险的差异无统计学意义。此外，CD4/CD8比值变化轨迹与非AIDS相关死亡的关联亦无统计学意义。见表4。
3　 讨论
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本研究共识别出启动ART的HIV感染者的两类CD4/CD8比值变化轨迹，与既往研究一致[9,11]。本研究中71.98%的HIV感染者CD4/CD8比值持续倒置，这与青少年感染者中63.6%[11]及成年感染者中62.2%[10]的CD4/CD8比值未能恢复至正常水平基本一致，表明CD4/CD8比值持续倒置在HIV感染者中普遍存在。CD4/CD8比值持续倒置，可能与HIV感染者体内持续的免疫激活和炎症状态有关[17]。研究证实CD4/CD8比值倒置是非艾滋病定义性疾病（如心血管疾病、恶性肿瘤）的重要预测指标[17]。这表明即使达到病毒抑制状态，大部分感染者仍长期处于共病高风险中。因此，未来应加强对HIV感染者的长期免疫监测，并将促进CD4/CD8比值正常化作为免疫重建的关键次级目标，以降低非艾滋病定义性疾病的发病风险。同时，对CD4/CD8比值持续倒置者，还应当加强心血管疾病和肿瘤的主动筛查和预防。
研究发现，与女性HIV感染者相比，男性更可能出现CD4/CD8比值持续倒置，与既往研究结果一致[6]，这种性别差异可能与性激素对免疫系统的调节作用有关[18]。经同性传播的HIV感染者也更易保持CD4/CD8比值持续倒置，这可能与无保护性行为、多性伴和性传播感染等可能引起肠相关淋巴组织损伤，促进细菌易位、加剧炎症反应，从而导致CD4/CD8比值下降有关[19-20]。因此，在评估HIV感染者免疫恢复状态时，除考虑启动ART时间和基线CD4计数水平等因素外，还需综合考虑性别、感染途径、性行为特征等因素，以制定个体化的ART方案和监测策略。启动ART时间>30 d的感染者更易出现CD4/CD8比值持续倒置，与既往研究结果一致[21]。研究表明，早期启动ART的HIV感染者，90%可在ART启动后6年内实现CD4/CD8比值正常化；而部分启动ART较晚的感染者，即使经过14年的有效病毒抑制且CD4计数>500 个/μl，CD4/CD8比值仍无法达到正常水平[18,22]，提示延迟启动ART所致的免疫损伤可能难以完全逆转。因此，应大力推行HIV感染的“早发现、早治疗”，缩短从确诊到ART启动的时间窗口，促进免疫系统功能恢复，改善感染者的长期预后。GLMMT结果进一步表明启动ART时间>30 d且基线CD4/CD8比值水平<1的HIV感染者是发生CD4/CD8比值持续倒置的高风险人群。对于此类感染者，即使实现病毒学抑制，仍需将其作为长期免疫监测与管理的重点人群，必要时考虑优化ART方案或辅助免疫干预。值得注意的是，即使在启动ART时间≤30 d的HIV感染者中，男性且基线CD4计数<200 个/μl者的CD4/CD8比值持续倒置比例仍高达73.85%。这提示，早期启动ART虽能降低整体风险，但男性且基线免疫严重受损者仍需重点监测。
本研究发现，CD4/CD8比值持续倒置组更可能发生AIDS相关死亡，与既往研究的结果一致[6]。CD4/CD8比值作为免疫重建的重要指标，其持续倒置往往提示机体免疫功能严重受损，会增加机会性感染和AIDS相关并发症的风险，导致HIV感染者死亡[1,17]。尽管部分研究报道低CD4/CD8比值与非AIDS相关死亡风险增加相关[6,23]，本研究未发现相关关联，非AIDS相关死亡（如心血管疾病、恶性肿瘤等）可能受多种复杂因素影响，CD4/CD8比值的单独预测价值可能有限[24]。未来研究应当进一步探索CD4/CD8比值与其他免疫标志物（如炎症因子、免疫激活指标）的联合作用对非AIDS相关死亡的影响，以明确CD4/CD8比值对HIV感染者非AIDS死亡风险的影响。
本研究存在局限性。首先，本研究仅纳入具有至少3次同时测量的CD4计数、CD8计数记录的HIV感染者，可能存在选择偏倚。其次，部分感染者的CD4计数、CD8计数数据存在缺失，导致数据连续性不足，这可能对CD4/CD8比值变化轨迹的模型拟合与分类准确性产生一定影响。再次，本研究未充分评估病毒抑制状态对免疫恢复的潜在影响。未来研究应纳入病毒载量等指标，更全面地评估病毒抑制状态在CD4/CD8比值恢复中的作用。最后，本研究中AIDS相关死亡事件数相对较少，亚组分析时事件数进一步减少，导致效应估计值的置信区间较宽，可能影响估计的精确性和稳定性。未来研究需扩大样本量、延长随访时间，以获取足够的结局事件数，提高效应估计的精确性和稳定性。
综上所述，在HIV感染者中，男性、同性传播感染、CD4/CD8比值持续倒置现象较为普遍。ART启动时间>30 d、基线CD4计数<200 个/μl及CD4/CD8比值<1是感染者CD4/CD8比值持续倒置的风险因素，因此在HIV感染早期启动ART对免疫重建至关重要，评估免疫状态时，要关注人口学及行为学因素的影响。CD4/CD8比值持续倒置与AIDS相关死亡显著正相关，在评估HIV感染者免疫功能和疾病进展时，不仅要关注CD4计数，还应关注CD4/CD8比值。
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  • 江苏省疾病预防控制局项目(JSJK2026M00006)
  • 无锡市卫生健康委项目(BJ2023097; FZXK2021010)
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参考文献 引证文献
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2026年第53卷第15期
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doi: 10.20043/j.cnki.MPM.202601451
  • 接收时间：2026-01-25
  • 首发时间：2026-09-28
  • 出版时间：2026-08-10
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  • 收稿日期：2026-01-25
基金
江苏省疾病预防控制局项目(JSJK2026M00006)
无锡市卫生健康委项目(BJ2023097; FZXK2021010)
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    无锡市疾病预防控制中心（南京医科大学附属无锡疾病预防控制中心），江苏 无锡 214023

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