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Statistical power and estimation of incidence rate ratios obtained from Bed incidence testing for evaluating HIV interventions among young people

机译:统计功效和从床位发病率测试中获得的发病率比率估计,用于评估年轻人的艾滋病干预措施

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摘要

Background: The objectives of this study were to determine the capacity of BED incidence testing to a) estimate the effect of a HIV prevention intervention and b) provide adequate statistical power, when used among young people from sub-Saharan African settings with high HIV incidence rates. Methods: Firstly, after having elaborated plausible scenarios based on empirical data and the characteristics of the BED HIV-1 Capture EIA (BED) assay, we conducted statistical calculations to determine the BED theoretical power and HIV incidence rate ratio (IRR) associated with an intervention when using BED incidence testing. Secondly, we simulated a cross-sectional study conducted in a population among whom an HIV intervention was rolled out. Simulated data were analyzed using a log-linear Poisson model to recalculate the IRR and its confidence interval, and estimate the BED practical power. Calculations were conducted with and without corrections for misclassifications. Results: Calculations showed that BED incidence testing can yield a BED theoretical power of 75% or more of the power that can be obtained in a classical cohort study conducted over a duration equal to the BED window period. Statistical analyses using simulated populations showed that the effect of a prevention intervention can be estimated with precision using classical statistical analysis of BED incidence testing data, even with an imprecise knowledge of the characteristics of the BED assay. The BED practical power was lower but of the same magnitude as the BED theoretical power. Conclusions: BED incidence testing can be applied to reasonably small samples to achieve good statistical power when used among young people to estimate IRR. © 2011 Auvert et al.
机译:背景:本研究的目的是确定BED发病率测试的能力,以便a)在来自撒哈拉以南非洲艾滋病毒高发地区的年轻人中使用时,估计艾滋病毒预防干预措施的效果,b)提供足够的统计能力。费率。方法:首先,在根据经验数据和BED HIV-1 Capture EIA(BED)分析的特征详细阐述了可能的情况后,我们进行了统计计算,以确定与BED相关的BED理论能力和HIV发生率(IRR)。使用BED发生率测试时进行干预。其次,我们模拟了一项针对人群的横断面研究,该人群中开展了HIV干预。使用对数线性泊松模型分析模拟数据,以重新计算IRR及其置信区间,并估算BED实用能力。进行计算时,可以对错误分类进行校正,也可以不进行校正。结果:计算表明,BED发生率测试可产生的BED理论功效为在等于BED窗口期的持续时间内进行的经典队列研究中可获得的功效的75%或更高。使用模拟人群进行的统计分析表明,使用BED发病率测试数据的经典统计分析,即使不了解BED分析的特征,也可以精确估算预防干预措施的效果。 BED的实际能力较低,但与BED的理论能力相同。结论:在年轻人中使用BED发生率测试来估计IRR时,可以将BED发生率测试应用于相当小的样本,以获得良好的统计功效。 ©2011 Auvert等。

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