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用功能主要组件分析对艾滋病毒感染者进行纵向病毒载荷聚类

Yunqing Ma¹, Xueying Yang^2,3, Jiayang Xiao¹

¹Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.

AIDS research and treatment

|February 14, 2025

概括

这项研究使用功能数据聚类来识别艾滋病毒感染者 (PWH) 的四种不同的病毒载荷模式. 这些模式,包括长期的病毒抑制和病毒失败,强调了需要个性化的艾滋病毒治疗策略.

科学领域:

免疫学免疫学免疫学
病毒学病毒学
数据科学数据科学数据科学

背景情况:

纵向病毒载量 (VL) 监测对于管理艾滋病毒状况至关重要.
关于对历史/纵向VL测量进行集群的研究有限.
分析VL模式提供了比聚合措施更深入的见解.

研究的目的:

使用功能数据集群对艾滋病毒感染者 (PWH) 的纵向VL模式进行分类.
通过人口统计,并发病,社会行为和CD4计数来描述已识别的集群.
为PWH提供量身定制的治疗和干预策略.

主要方法:

分析了在南卡罗来纳州2005-2015年诊断的成人PWH,随访时间>=5年.
功能主要组件分析 (FPCA) 用于分类,优于其他方法.
ANOVA在集群中比较了VL特征,人口统计,并发症,物质使用和CD4计数.

主要成果:

FPCA确定了四种不同的VL模式:长期病毒抑制 (17.3%),短期病毒抑制 (29.8%),次优病毒抑制 (28.3%) 和病毒失败 (24.9%).
病毒失败组显示了较高的平均VL和较低的平均CD4计数.
在四个确定的集群中,人口和临床特征在四个确定的集群中差异很大.

结论:

功能数据集群有效地区分PWH中的不同病毒配置文件.
了解这些独特的模式对于开发有针对性的干预措施至关重要.
个性化治疗方法对于优化所有PWH的结果至关重要.

关键词:

这是FPCA.艾滋病病毒艾滋病病毒艾滋病病毒南卡罗来纳州南卡罗来纳州纵向的 VL 集群.

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