Andualem Belay Desyebelew, Ayele Birhanu Teshome
Department of Statistics, Dire Dawa University, Dire Dawa, Ethiopia.
Department of Statistics, Addis Ababa University, Addis Ababa, Ethiopia.
Front Public Health. 2020 Feb 19;7:415. doi: 10.3389/fpubh.2019.00415. eCollection 2019.
Although the world has been fighting HIV disease in unity and patients are getting antiretroviral therapy treatment, HIV disease continues to be a serious health issue for some parts of the world. A large number of AIDS-related deaths and co-morbidities are registered every year in resource-limited countries like Ethiopia. Most studies that have assessed the progression of the disease have used models that required a continuous response. The main objective of this study was to make use of appropriate statistical models to analyze routinely collected HIV data and identify risk factors associated with the progression of the CD4 cell count of patients under ART treatment in Debre Markos Referral Hospital, Ethiopia. In this longitudinal retrospective study, routine data of 445 HIV patients registered for ART treatment in the Hospital were used. As overdispersion was detected in the data, and Poisson-Gamma, Poisson-Normal, and Poisson-Gamma-Normal models were applied to account for overdispersion and correlation in the data. The Poisson-Gamma-Normal model with a random intercept was selected as the best model to fit the data. The findings of the study revealed the time on treatment, sex of patients, baseline WHO stage, and baseline CD4 cell count as significant factors for the progression of the CD4 cell count.
尽管全世界一直在共同抗击艾滋病,患者也在接受抗逆转录病毒治疗,但艾滋病在世界某些地区仍然是一个严重的健康问题。在埃塞俄比亚等资源有限的国家,每年都有大量与艾滋病相关的死亡和合并症记录在案。大多数评估该疾病进展的研究都使用了需要连续反应的模型。本研究的主要目的是利用适当的统计模型来分析常规收集的艾滋病数据,并确定埃塞俄比亚德布雷马科斯转诊医院接受抗逆转录病毒治疗的患者CD4细胞计数进展的相关危险因素。在这项纵向回顾性研究中,使用了该医院登记接受抗逆转录病毒治疗的445名艾滋病患者的常规数据。由于在数据中检测到过度离散,因此应用泊松-伽马、泊松-正态和泊松-伽马-正态模型来处理数据中的过度离散和相关性。选择具有随机截距的泊松-伽马-正态模型作为拟合数据的最佳模型。研究结果表明,治疗时间、患者性别、基线世界卫生组织分期和基线CD4细胞计数是CD4细胞计数进展的重要因素。