Khorashadizadeh Fatemeh, Tabesh Hamed, Parsaeian Mahboubeh, Esmaily Habibollah, Rahimi Foroushani Abbas
Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Iran J Public Health. 2020 May;49(5):949-958.
The present study aimed to estimate the survival of HIV-positive patients and compare the accuracy of two commonly used models, Shared Random-Effect Model (SREM) and Joint Latent Class Model (JLCM) for the analysis of time to death among these patients.
Data on a retrospective survey among HIV-positive patients diagnosed during 1989-2014 who referred to the Behavioral Diseases Consultation Center of Mashhad University of Medical Sciences was used in this study. Participants consisted of HIV-positive high-risk volunteers, referrals of new HIV cases from prisons, blood transfusion organization and hospitals. Subjects were followed from diagnosis until death or the end of study. SREM and JLCM were used to predict the survival of HIV/AIDS patients. In both models age, sex and addiction were included as covariates. To compare the accuracy of these alternative models, dynamic predictions were calculated at specific time points. The receiver operating characteristic (ROC) curve was used to select the more accurate model.
Overall, 213 patients were eligible that met entry conditions for the present analysis. Based on BIC criteria, three heterogeneous sub-populations of patients were identified by JLCM and individuals were categorized in these classes ("High Risk", "Moderate Risk" and "Low Risk") according to their health status. JLCM had a better predictive accuracy than SREM. The average area under ROC curve for JLCM and SREM was 0.75 and 0.64 respectively. In both models CD4 count decreased with time. Based on the result of JLCM, men had higher hazard rate than women and the CD4 counts levels of patients decreased with increasing age.
Predicting risk of death (or survival) is vital for patients care in most medical research. In a heterogeneous population, such as HIV-positive patients fitting JLCM can significantly improve the accuracy of the risk prediction. Therefore, this model is preferred for these populations.
本研究旨在评估HIV阳性患者的生存率，并比较两种常用模型——共享随机效应模型（SREM）和联合潜在类别模型（JLCM）在分析这些患者死亡时间方面的准确性。
本研究使用了对1989年至2014年期间转诊至马什哈德医科大学行为疾病咨询中心的HIV阳性患者进行回顾性调查的数据。参与者包括HIV阳性的高危志愿者、来自监狱、输血机构和医院的新HIV病例转诊者。从诊断开始对受试者进行随访，直至死亡或研究结束。使用SREM和JLCM预测HIV/AIDS患者的生存率。在这两种模型中，年龄、性别和成瘾情况作为协变量纳入。为了比较这些替代模型的准确性，在特定时间点计算动态预测值。使用受试者工作特征（ROC）曲线选择更准确的模型。
总体而言，213名患者符合本分析的纳入条件。根据BIC标准，JLCM识别出三个异质性患者亚群，并根据个体健康状况将其分为这些类别（“高风险”、“中度风险”和“低风险”）。JLCM的预测准确性优于SREM。JLCM和SREM的ROC曲线下平均面积分别为0.75和0.64。在两种模型中，CD4计数均随时间下降。根据JLCM的结果，男性的风险率高于女性，且患者的CD4计数水平随年龄增加而下降。
在大多数医学研究中，预测死亡风险（或生存率）对患者护理至关重要。在异质性人群中，如HIV阳性患者，拟合JLCM可显著提高风险预测的准确性。因此，该模型更适用于这些人群。
