Hanson Debra L, Song Ruiguang, Masciotra Silvina, Hernandez Angela, Dobbs Trudy L, Parekh Bharat S, Owen S Michele, Green Timothy A
Quantitative Sciences and Data Management Branch, Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Laboratory Branch, Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
PLoS One. 2016 Apr 11;11(4):e0152327. doi: 10.1371/journal.pone.0152327. eCollection 2016.
HIV incidence estimates are used to monitor HIV-1 infection in the United States. Use of laboratory biomarkers that distinguish recent from longstanding infection to quantify HIV incidence rely on having accurate knowledge of the average time that individuals spend in a transient state of recent infection between seroconversion and reaching a specified biomarker cutoff value. This paper describes five estimation procedures from two general statistical approaches, a survival time approach and an approach that fits binomial models of the probability of being classified as recently infected, as a function of time since seroconversion. We compare these procedures for estimating the mean duration of recent infection (MDRI) for two biomarkers used by the U.S. National HIV Surveillance System for determination of HIV incidence, the Aware BED EIA HIV-1 incidence test (BED) and the avidity-based, modified Bio-Rad HIV-1/HIV-2 plus O ELISA (BRAI) assay. Collectively, 953 specimens from 220 HIV-1 subtype B seroconverters, taken from 5 cohorts, were tested with a biomarker assay. Estimates of MDRI using the non-parametric survival approach were 198.4 days (SD 13.0) for BED and 239.6 days (SD 13.9) for BRAI using cutoff values of 0.8 normalized optical density and 30%, respectively. The probability of remaining in the recent state as a function of time since seroconversion, based upon this revised statistical approach, can be applied in the calculation of annual incidence in the United States.
HIV发病率估计值用于监测美国的HIV-1感染情况。使用能够区分近期感染与长期感染的实验室生物标志物来量化HIV发病率,这依赖于准确了解个体在血清转化和达到特定生物标志物临界值之间处于近期感染短暂状态的平均时间。本文描述了来自两种一般统计方法的五种估计程序,一种是生存时间方法,另一种是拟合作为血清转化后时间函数的被归类为近期感染概率的二项式模型的方法。我们比较了这些程序,以估计美国国家HIV监测系统用于确定HIV发病率的两种生物标志物的近期感染平均持续时间(MDRI),即Aware BED EIA HIV-1发病率检测(BED)和基于亲和力的改良Bio-Rad HIV-1/HIV-2 plus O ELISA(BRAI)检测。总共对来自5个队列的220名HIV-1 B亚型血清转化者的953份标本进行了生物标志物检测。使用非参数生存方法估计的MDRI,对于BED,使用0.8归一化光密度的临界值,为198.4天(标准差13.0);对于BRAI,使用30%的临界值,为239.6天(标准差13.9)。基于这种修订后的统计方法,作为血清转化后时间函数的保持在近期状态的概率可应用于美国年发病率的计算。