A Parsimonious Host Inflammatory Biomarker Signature Predicts Incident Tuberculosis And Mortality In Advanced Human Immunodeficiency Virus

CLINICAL INFECTIOUS DISEASES(2020)

引用 12|浏览43
暂无评分
摘要
Background. People with advanced human immunodeficiency virus (HIV) (CD4 < 50) remain at high risk of tuberculosis (TB) or death despite the initiation of antiretroviral therapy (ART). We aimed to identify immunological profiles that were most predictive of incident TB disease and death.Methods. The REMEMBER randomized clinical trial enrolled 850 participants with HIV (CD4 < 50 cells/mu l) at ART initiation to receive either empiric TB treatment or isoniazid preventive therapy (IPT). A case-cohort study (n = 257) stratified by country and treatment arm was performed. Cases were defined as incident TB or all-cause death within 48 weeks after ART initiation. Using multiplexed immunoassay panels and ELISA, 26 biomarkers were assessed in plasma.Results. In total, 52 (6.1%) of 850 participants developed TB; 47 (5.5%) died (13 of whom had antecedent TB). Biomarkers associated with incident TB overlapped with those associated with death (interleukin [11,]-1 beta, IL-6). Biomarker levels declined over time in individuals with incident TB while remaining persistently elevated in those who died. Dividing the cohort into development and validation sets, the final model of 6 biomarkers (CXCLIO, IL- 1 beta, IL-10, sCD14, tumor necrosis factor [TNF] -alpha, and TNF-beta) achieved a sensitivity of 0.90 (95% confidence interval [CI]: .87-.94) and a specificity of 0.71(95% CI: .68-.75) with an area under the curve (AUC) of 0.81 (95% CI: .78-.83) for incident TB.Conclusion. Among people with advanced HIV, a parsimonious inflammatory biomarker signature predicted those at highest risk for developing TB despite initiation of ART and TB preventive therapies. The signature may be a promising stratification tool to select patients who may benefit from increased monitoring and novel interventions.
更多
查看译文
关键词
tuberculosis, biomarker, antiretroviral therapy, early mortality
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要