Department of Statistical Sciences, University of Cape Town, Rondebosch South Africa.
J Biopharm Stat. 2020;30(1):197-215. doi: 10.1080/10543406.2019.1632875. Epub 2019 Jun 27.
In this paper, we assess the effect of tuberculosis pericarditis treatment (prednisolone) on CD4 count changes over time and draw inferences in the presence of missing data. We accounted for the missing data and performed sensitivity analyses to assess robustness of inferences, from a model that assumes that the data are missing at random, to models that assume that the data are not missing at random. Our sensitivity approaches are within the shared-parameter model framework. We implemented the approach by Creemers and colleagues to the CD4 count data and performed simulation studies to evaluate the performance of this approach. We also assessed the influence of potentially influential subjects, on parameter estimates, via the global influence approach. Our results revealed that inferences from missing at random analysis model are robust to not missing at random models and influential subjects did not overturn the study conclusions about prednisolone effect and missing data mechanism. Prednisolone was found to have no significant effect on CD4 count changes over time and also did not interact with anti-retroviral therapy. The simulation studies produced unbiased estimates of prednisolone effect with lower mean square errors and coverage probabilities approximately equal the nominal coverage probability.
在本文中，我们评估了结核性心包炎治疗（泼尼松龙）对 CD4 计数随时间变化的影响，并在存在缺失数据的情况下进行了推断。我们考虑了缺失数据，并进行了敏感性分析，以评估在数据随机缺失和非随机缺失的假设下，推断的稳健性。我们的敏感性方法属于共享参数模型框架。我们将 Creemers 及其同事的方法应用于 CD4 计数数据，并进行了模拟研究，以评估该方法的性能。我们还通过全局影响方法评估了潜在有影响的个体对参数估计的影响。我们的结果表明，随机缺失分析模型的推断对非随机缺失模型是稳健的，有影响的个体并没有推翻关于泼尼松龙作用和缺失数据机制的研究结论。泼尼松龙对 CD4 计数随时间的变化没有显著影响，也与抗逆转录病毒治疗没有相互作用。模拟研究产生了泼尼松龙效应的无偏估计，均方误差较低，覆盖率概率接近名义覆盖率概率。
