Dagne Getachew A, Ibrahimou Boubakari
a Department of Epidemiology & Biostatistics , College of Public Health, University of South Florida , Tampa , Florida , USA.
b Robert Stempel College of Public Health & Social Work , Florida International University , Miami , Florida , USA.
J Biopharm Stat. 2017;27(4):691-704. doi: 10.1080/10543406.2016.1269782. Epub 2016 Dec 23.
A major problem in HIV/AIDS studies is the development of drug resistance to antiretroviral (ARV) drug or therapy. Estimating the time at which such drug resistance would develop is usually sought. The goal of this article is to perform this estimation by developing growth mixture models with change-points and skew-t distributions based on longitudinal data. For such data, following ARV treatment, the profile of each subject's viral load tends to follow a 'broken stick' like growth trajectory, indicating multiple phases of decline and increase in viral loads. These multiple phases with multiple change-points are captured by subject-specific random parameters of growth curve models. To account for heterogeneity of drug resistance among subjects, the change-points are also allowed to differ by subgroups (subpopulations) of patients classified into latent classes on the basis of trajectories of observed viral loads. The proposed methods are illustrated using real data from an AIDS clinical study.
艾滋病病毒/艾滋病研究中的一个主要问题是对抗逆转录病毒（ARV）药物或疗法产生耐药性。通常需要估计产生这种耐药性的时间。本文的目标是通过基于纵向数据开发具有变点和偏态t分布的生长混合模型来进行这种估计。对于此类数据，在接受抗逆转录病毒治疗后，每个受试者的病毒载量曲线往往遵循“折断的棍子”状的生长轨迹，表明病毒载量有多个下降和上升阶段。生长曲线模型的个体特定随机参数捕捉了这些具有多个变点的多个阶段。为了考虑受试者之间耐药性的异质性，还允许变点因根据观察到的病毒载量轨迹分类为潜在类别的患者亚组（亚群体）而有所不同。使用来自一项艾滋病临床研究的真实数据说明了所提出的方法。
