Combining CD4 count, CD8 count and CD4/CD8 ratio to predict risk of mortality among HIV-positive adults after therapy: a group-based multi-trajectory analysis

Jing Ma; Guoyong Wang; Xiaoyan Zhu; Ling Li; Lin Wang; Lianzheng Hao; Lijie Gao; Wei Ma; Na Zhang

doi:10.3389/fimmu.2023.1269650

Combining CD4 count, CD8 count and CD4/CD8 ratio to predict risk of mortality among HIV-positive adults after therapy: a group-based multi-trajectory analysis

Front Immunol. 2023 Dec 6:14:1269650. doi: 10.3389/fimmu.2023.1269650. eCollection 2023.

Authors

Jing Ma^#^{1

2}, Guoyong Wang^#^{2

3}, Xiaoyan Zhu^{2

3}, Ling Li^{2

3}, Lin Wang^{2

3}, Lianzheng Hao^{2

3}, Lijie Gao^{1

2}, Wei Ma^{1

2}, Na Zhang^{2

3}

Affiliations

¹ Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
² Institute of Preventive Medicine, Shandong University, Jinan, Shandong, China.
³ Institute for Acquired Immunodeficiency Syndrome (AIDS) Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China.

^# Contributed equally.

Abstract

Introduction: Previous studies have indicated different immunological recovery trajectories based on CD4 count or CD4/CD8 ratio. However, these immune indicators are interconnected, and relying solely on one indicator may lead to inaccurate estimates. Therefore, it is essential to develop a comprehensive trajectory model that integrates CD4 count, CD8 count and CD4/CD8 ratio.

Methods: We utilized a group-based multi-trajectory model to characterize the latent cluster of recovery based on measurements of CD4 count, CD8 count and CD4/CD8 ratio over a period of up to 96 months following ART initiation. Subsequently, we investigated the characteristics associated with trajectory groups, especially sex and age. Cox model and Kaplan-Meier survival curve were employed to assess differences in all-cause, AIDS-related and non-AIDS related mortality between trajectory groups.

Results: A total of 14,718 eligible individuals were followed for a median of 55 months. Longitudinal model identified four subgroups: group 1 (32.5%, low CD4 and CD4/CD8 inversion), group 2 (25.9%, high CD8 and CD4/CD8 inversion), group 3 (27.2%, slow recovery of CD4 and CD4/CD8 inversion) and group 4 (14.4%, rapid increase of CD4 and normal CD4/CD8). Immune recovery was slower in male than in female, and in elders than in youngers. Compared to group 2, group 1 (adjusted hazard ratio [aHR]=3.28; 95% CI 2.33-4.60) and group 3 (aHR=1.56; 95% CI 1.09-2.24) had increased risk of all-cause mortality after adjusting for other factors. Besides, group 1 (aHR=2.17) and group 3 (aHR=1.58) had higher risk of non-AIDS related mortality, and group 1 (aHR=5.92) had significantly increased risk of AIDS related mortality.

Conclusion: Longitudinal trajectory analysis of multiple immune indicators can be employed to guide targeted interventions among vulnerable populations in clinical practice.

Keywords: CD4 count; CD4/CD8 ratio; CD8 count; HIV; antiretroviral therapy; mortality.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Acquired Immunodeficiency Syndrome* / drug therapy
Adult
Aged
Anti-HIV Agents* / therapeutic use
CD4 Lymphocyte Count
CD8-Positive T-Lymphocytes
Female
HIV Infections*
HIV Seropositivity* / drug therapy
Humans
Male

Substances

Anti-HIV Agents

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Key Research and Development Program of China (grant number 2022YFC2304905 and 2017YFE0103800), Shandong Provincial Natural Science Foundation Youth Program (grant number ZR2014HQ038) and Shandong Provincial Medical and Health Science and Technology Development Program (grant number 2019WS438). The funders of this study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report.