School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg, 3209, South Africa.
Institute of Human Virology, School of Medicine, University of Maryland, Baltimore, MD, USA.
Sci Rep. 2020 Oct 7;10(1):16742. doi: 10.1038/s41598-020-73883-7.
It is of great interest for a biomedical analyst or an investigator to correctly model the CD4 cell count or disease biomarkers of a patient in the presence of covariates or factors determining the disease progression over time. The Poisson mixed-effects models (PMM) can be an appropriate choice for repeated count data. However, this model is not realistic because of the restriction that the mean and variance are equal. Therefore, the PMM is replaced by the negative binomial mixed-effects model (NBMM). The later model effectively manages the over-dispersion of the longitudinal data. We evaluate and compare the proposed models and their application to the number of CD4 cells of HIV-Infected patients recruited in the CAPRISA 002 Acute Infection Study. The results display that the NBMM has appropriate properties and outperforms the PMM in terms of handling over-dispersion of the data. Multiple imputation techniques are also used to handle missing values in the dataset to get valid inferences for parameter estimates. In addition, the results imply that the effect of baseline BMI, HAART initiation, baseline viral load, and the number of sexual partners were significantly associated with the patient's CD4 count in both fitted models. Comparison, discussion, and conclusion of the results of the fitted models complete the study.
对于生物医学分析人员或研究人员来说，在存在决定疾病随时间进展的协变量或因素的情况下，正确地对患者的 CD4 细胞计数或疾病生物标志物进行建模是非常重要的。泊松混合效应模型（PMM）可以作为重复计数数据的合适选择。然而，由于均值和方差相等的限制，该模型并不现实。因此，PMM 被负二项混合效应模型（NBMM）所取代。后一种模型有效地处理了纵向数据的过离散性。我们评估并比较了所提出的模型及其在招募于 CAPRISA 002 急性感染研究的 HIV 感染患者的 CD4 细胞数量中的应用。结果表明，NBMM 具有适当的性质，并在处理数据的过离散性方面优于 PMM。还使用多重插补技术处理数据集的缺失值，以便对参数估计进行有效的推断。此外，结果表明，在拟合模型中，基线 BMI、HAART 起始、基线病毒载量和性伴侣数量与患者的 CD4 计数显著相关。拟合模型的结果比较、讨论和结论完成了这项研究。
