A Comparative Study of Different Joint Modeling Approaches for HIV/AIDS Patients in Southern Iran

BACKGROUND: The prevalence of HIV/AIDS has been increasing in Iran, especially amongst the young population, recently. The joint model (JM) is a statistical method that represents an effective strategy to incorporate all information of repeated measurements and survival outcomes simultaneously. In many theoretical studies, the population under the study were heterogeneous. This study aimed at comparing three approaches by considering heterogeneity in the patients. METHODS: This study was conducted on 750 archived files of patients infected with HIV in Fars Province, southern Iran, from 1994 to 2017. Proposed Approach (PA), Joint Latent Class Models (JLCM), and Separated Approach (SA) were compared to evaluate the influence covariates on the longitudinal and time-to-event outcomes in the heterogeneous HIV/AIDS patients. RESULTS: Gender (P<0.001) and HCV (P<0.01) were two significant covariates in the classification of HIV/AIDS patients. Time had a significant effect on CD4 (P<0.001) in both classes in the three approaches. In PA and SA, females had higher CD4 than males (P<0.001) in the first class. In JLCM, females had higher CD4 than males (P<0.01) in both classes. The patients with higher Hgb had also higher CD4 (P<0.001) in both classes in the three approaches. HCV reduced the CD4 significantly in both classes in PA (P<0.05) and SA (P<0.001). Within the survival sub-model, HCV reduced survival rate significantly in the second class in PA (P<0.05), JLCM (P<0.01) and SA (P<0.001). CONCLUSION: PA was an appropriate approach for joint modeling longitudinal and survival outcomes for this heterogeneous population.