Estimating the odds ratio when exposure has a limit of detection

Estimating the odds ratio when exposure has a limit of detection
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DOI:
10.1093/ije/dyp269
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发表时间:
2009-12-01
影响因子:
7.7
通讯作者:
Schisterman, Enrique F.
Schisterman, Enrique F.
中科院分区:
医学1区
文献类型:
--
作者:
Cole, Stephen R.;Chu, Haitao;Schisterman, Enrique F.

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我们使用五种方法,包括特别方法和最大似然估计(MLE),计算了45名HIV感染男性的抗HIV治疗初期的几率,作为测量的log(10)血浆HIV RNA病毒载量的函数。我们还模拟了二元结果,在对数正态分布暴露中,10%的发生率和每对数增加1.5倍的几率,暴露数据的25%、50%和75%低于LOD。模拟数据分析使用相同的五种方法,以及完整的数据。在本例中,估计的比值比(OR)在不同方法之间变化了1.22倍,从1.45到1.77每对数(10)个病毒载量拷贝,对数OR的标准误差在不同方法之间变化了1.52倍,从0.31到0.47。在模拟中,使用完整数据或最大似然是无偏的,具有适当的置信区间(CI)覆盖率。然而,随着低于LOD暴露比例的增加,替代LOD、LOD/root 2或LOD/2的偏差越来越大,CI覆盖率也越来越不合适。最后,排除低于LOD的值是无偏的,但不精确。在本例和模拟探索的设置中,以及在研究人员可用的方法中(即没有完整数据),MLE提供了对暴露-结果OR的无偏和适当精确的估计。
Methods We calculate the odds of anti-HIV therapy naivete in 45 HIV-infected men as a function of measured log(10) plasma HIV RNA viral load using five approaches including ad hoc methods as well as a maximum likelihood estimate (MLE). We also generated simulations of a binary outcome with 10% incidence and a 1.5-fold increased odds per log increase in a log-normally distributed exposure with 25, 50 and 75% of exposure data below LOD. Simulated data were analysed using the same five methods, as well as the full data.Results In the example, the estimated odds ratio (OR) varied by 1.22-fold across methods, from 1.45 to 1.77 per log(10) copies of viral load and the standard error for the log OR varied by 1.52-fold across methods, from 0.31 to 0.47. In the simulations, use of full data or the MLE was unbiased with appropriate confidence interval (CI) coverage. However, as the proportion of exposure below LOD increased, substituting LOD, LOD/root 2 or LOD/2 was increasingly biased with increasingly inappropriate CI coverage. Finally, exclusion of values below LOD was unbiased but imprecise.Conclusions In this example and the settings explored by simulation, and among methods readily available to investigators (i.e. sans full data), the MLE provided an unbiased and appropriately precise estimate of the exposure-outcome OR.