Comparison of HIV type 1 incidence observed during longitudinal follow-up with incidence estimated by cross-sectional analysis using the BED capture enzyme immunoassay
Comparison of HIV type 1 incidence observed during longitudinal follow-up with incidence estimated by cross-sectional analysis using the BED capture enzyme immunoassay
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DOI：
10.1089/aid.2006.22.945
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发表时间：
2006-10-01
影响因子：
1.5
通讯作者：
Gurwith, Marc
中科院分区：
文献类型：
--
作者：
McDougal, J. Steven;Parekh, Bharat S.;Gurwith, Marc
BED捕获酶免疫测定法（BED CEIA）用于近期感染，用于估计来自单一横断面调查的人群中的HIV-1发病率。为了评价性能，我们将该检测方法应用于从纵向队列研究（AIDSVAX B/B疫苗试验）中获得的标本集，该试验对观察到的发病率进行了独立和常规的测量。对每6个月进行一次血清转换随访期间获得的标本进行BED CEIA，持续3年。在所有时间间隔内，观察到的发病率与床估计的发病率之间具有极好的一致性。在队列中观察到的累积年发生率为3.10例新发感染/100人-年（95% CI，2.57-3.63）。相应的BED估计发生率为2.91（2.30-3.53）。我们还估计了不同的患病率对固定发病率的影响。由于检测试剂盒将长期感染者的一些标本归类为近期样本，因此可能会夸大发病率估计值。我们量化了这种影响，并讨论了潜在的缓解措施，排除某些标本的临床理由，依靠趋势差异，而不是绝对的发病率估计，通过二次确证性测试，或分析调整错误分类。横断面艾滋病毒发病率估计规避了许多与纵向队列研究相关的缺点，但在设计人口调查时应考虑特定的测试限制。
The BED capture enzyme immunoassay (BED CEIA) for recent infection was developed for the estimation of HIV-1 incidence in a population from a single cross-sectional survey. To evaluate performance, we applied the assay to specimen sets obtained from a longitudinal cohort study, the AIDSVAX B/B vaccine trial, in which there was an independent and conventional measure of observed incidence. The BED CEIA was performed on specimens obtained during follow-up for seroconversion conducted every 6 months for 3 years. There was excellent agreement between the observed and BED- estimated incidence for all the intervals. The cumulative, annualized incidence observed in the cohort was 3.10 new infections per 100 person-years (95% CI, 2.57-3.63). The corresponding BED- estimated incidence was 2.91 (2.30-3.53). We also estimated the effect of varied prevalence on a fixed incidence. Because some specimens from persons with longer-term infection are classified as recent by the assay, this can inflate the incidence estimate. We quantify this effect and discuss potential mitigation by excluding certain specimens on clinical grounds, by relying on trend differences rather than absolute incidence estimates, by secondary confirmatory testing, or by analytic adjustments for misclassification. Cross-sectional HIV incidence estimation circumvents many of the drawbacks associated with longitudinal cohort studies, but there are test-specific limitations that should be considered in the design of population surveys.