反复事件与相关信息审查的分析:在HIV数据中的应用

Jonathan Ejoku, C. Odhiambo, Linda Chaba
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引用次数: 3

摘要

在这项研究中,我们采用基于cox的模型来研究复发事件;普伦蒂斯,威廉姆斯和彼得森总时间(PWP-TT),主要是在非信息审查假设下使用的,并在信息审查设置下对其进行评估。借助于Huang[1]提出的循环事件半参数框架进行实证评估,并在R Studio软件中实现。为了验证,我们使用了肯尼亚一个典型的艾滋病护理机构的数据。在审议中的三种模式中;标准Cox模型的性别风险比(HR)为0.66 (p值=0.165),Andersen-Gill模型的HR为0.46(临界p值=0.054),扩展PWP TT的HR为0.22 (p值=0.006)。与其他模型相比,PWP-TT模型在信息设置下表现更好。在信息环境下的风险因素方面,LTFU是由于耻辱;性别[基数=男性]的HR为0.544 (p值=0.002),年龄[基数< 37]的HR为0.772 (p值=0.008),ART方案[基数=一线]的HR为0.518 (p值= 0.233),差异化护理模式(基数=非DCM)的HR为0.77(p值=0.036)。总之,尽管有多种干预措施旨在解决艾滋病毒患者中LTFU的发生率,但LTFU的个人病例通常是常见的和复发性的,目前一个人获得LTFU的可能性受到先前事件的影响,因此应检查信息审查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Recurrent Events with Associated Informative Censoring: Application to HIV Data
In this study, we adapt a Cox-based model for recurrent events; the Prentice, Williams and Peterson Total -Time (PWP-TT) that has largely, been used under the assumption of non-informative censoring and evaluate it under an informative censoring setting. Empirical evaluation was undertaken with the aid of the semi-parametric framework for recurrent events suggested by Huang [1] and implemented in R Studio software. For validation we used data from a typical HIV care setting in Kenya. Of the three models under consideration; the standard Cox Model had gender hazard ratio (HR) of 0.66 (p-value=0.165), Andersen-Gill had HR 0.46 (with borderline p-value=0.054) and extended PWP TT had HR 0.22 (p-value=0.006). The PWP-TT model performed better as compared to other models under informative setting. In terms of risk factors under informative setting, LTFU due to stigma; gender [base=Male] had HR 0.544 (p-value =0.002), age [base is < 37] had HR 0.772 (p-value=0.008), ART regimen [base= First line] had HR 0.518 (p-value= 0.233) and differentiated care model (Base=not on DCM) had HR 0.77(p-value=0.036). In conclusion, in spite of the multiple interventions designed to address incidences of LTFU among HIV patients, within-person cases of LTFU are usually common and recurrent in nature, with the present likelihood of a person getting LTFU influenced by previous occurrences and therefore informative censoring should be checked.
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