Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive Accuracy
Background: 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. Methods: Data on a retrospectiv...
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| Format: | Article |
| Language: | English |
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Tehran University of Medical Sciences
2020-05-01
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| Series: | Iranian Journal of Public Health |
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| Online Access: | https://ijph.tums.ac.ir/index.php/ijph/article/view/15083 |
| _version_ | 1818864606989254656 |
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| author | Fatemeh KHORASHADIZADEH Hamed TABESH Mahboubeh PARSAEIAN Habibollah ESMAILY Abbas RAHIMI FOROUSHANI |
| author_facet | Fatemeh KHORASHADIZADEH Hamed TABESH Mahboubeh PARSAEIAN Habibollah ESMAILY Abbas RAHIMI FOROUSHANI |
| author_sort | Fatemeh KHORASHADIZADEH |
| collection | DOAJ |
| description | Background: 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.
Methods: 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.
Results: 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.
Conclusion: 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. |
| first_indexed | 2024-12-19T10:34:20Z |
| format | Article |
| id | doaj.art-61bb5a2de19f4ceea4db51fd656a3717 |
| institution | Directory Open Access Journal |
| issn | 2251-6085 2251-6093 |
| language | English |
| last_indexed | 2024-12-19T10:34:20Z |
| publishDate | 2020-05-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | Iranian Journal of Public Health |
| spelling | doaj.art-61bb5a2de19f4ceea4db51fd656a37172022-12-21T20:25:40ZengTehran University of Medical SciencesIranian Journal of Public Health2251-60852251-60932020-05-01495Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive AccuracyFatemeh KHORASHADIZADEH0Hamed TABESH1Mahboubeh PARSAEIAN2Habibollah ESMAILY3Abbas RAHIMI FOROUSHANI4Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, IranDepartment of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, IranDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, IranSocial Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, IranDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, IranBackground: 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. Methods: 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. Results: 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. Conclusion: 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.https://ijph.tums.ac.ir/index.php/ijph/article/view/15083ROC curve;HIVJoint latent class model;Shared random effect model |
| spellingShingle | Fatemeh KHORASHADIZADEH Hamed TABESH Mahboubeh PARSAEIAN Habibollah ESMAILY Abbas RAHIMI FOROUSHANI Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive Accuracy Iranian Journal of Public Health ROC curve; HIV Joint latent class model; Shared random effect model |
| title | Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive Accuracy |
| title_full | Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive Accuracy |
| title_fullStr | Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive Accuracy |
| title_full_unstemmed | Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive Accuracy |
| title_short | Predicting the Survival of AIDS Patients Using Two Frameworks of Statistical Joint Modeling and Comparing Their Predictive Accuracy |
| title_sort | predicting the survival of aids patients using two frameworks of statistical joint modeling and comparing their predictive accuracy |
| topic | ROC curve; HIV Joint latent class model; Shared random effect model |
| url | https://ijph.tums.ac.ir/index.php/ijph/article/view/15083 |
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