Mahsa Nazari, Farid Zayeri , Seyed Saeed Hashemi Nazari , Sara Jambarsang, Ali Nikfarjam , Alireza Akbarzadeh Baghban ,
Volume 77, Issue 2 (5-2019)
Abstract
Background: The Multi state Markov models have extensively application with categorization of laboratory marker of CD4 cells for evaluation of HIV disease progression. These models with different states result in different effects of covariates and prediction of HIV disease trend. The main purpose of this study was comparison of four and five states models with the three- state in order to select the model with better prediction ability of occurrence of HIV and finally death in HIV positive people.
Methods: A total of 305 HIV positive people were included in this cohort study in the Iran AIDS center in Imam Khomeini Hospital in Tehran that entered during March 1995 to January 2005 and then fallowed up to October 2014. The three continuous- time Markov models of three-, four- and five- state models were fitted to data to describe the evolution of a HIV disease Trend over different states.
For comparison of models, two criteria of modification of Akaike’s criterion (DRAIC) and likelihood cross-validation criterion (DRLCV) along with their 95% tracking interval was used. For fitting of these models and estimation of transition matrix and the hazard ratio of gender and treatment independent variables, the msm package of R project for statistical computing, version R 3.2.4 (www.r-project.org) was used.
Results: The results showed that the four- state model has more prediction ability than five-state model for evaluation of HIV disease Trend. In the four-state model, the progression hazard ratio to death for people who received highly active antiretroviral therapy (HAART) was 0.64 lower than who didn’t get this therapy. Moreover, the progression hazard ratio for men was 2.33 fold in comparison to women. The disease progression hazard ratio to death was 4.9 fold for men in comparison to women.
Conclusion: The (DRAIC) and (DRLCV) criterions showed that the four-state model has more predictive ability of the progression trend of HIV disease in comparison of five-state model.
Saedeh Ebrahimi, Saeed Kalantari , Soheil Rahmani Fard , Mitra Kohandel, Zahra Amiri, Yousef Alimohamadi , Sara Minaeian,
Volume 80, Issue 2 (5-2022)
Abstract
Background: Despite the considerable advances in acquired immunodeficiency syndrome (AIDS) treatment and management, finding the cure for this disease has been hindered by emerging challenges such as virus resistance and treatment failures. The purpose of this study is to compare the cytokine profiles of patients with successful treatment and patients with unsuccessful treatment to gain a better understanding of treatment failure mechanisms.
Methods: Sixty-nine human immunodeficiency virus (HIV) positive patients who were referred to the west health center of Tehran between September 2018 and March 2021 were included in this study. Blood CD4+ cell count and viral load was measured using the flow cytometry and quantitative real-time polymerase chain reaction (RT-qPCR) methods respectively. Based on the viral load test results patients were divided into successful treatment (viral load<200 copies/ml, n=36) and unsuccessful treatment (viral load>200 copies/ml, n=33) groups. Subsequently, tumor necrosis factor-α (TNF-α) and interleukin-10 (IL-10) serum levels were measured using the enzyme-linked immunosorbent assay (ELISA) method.
Results: Analysis of data revealed that there was no difference in demographic data, medical history and clinical laboratory test results between the study groups. Elisa test results showed that serum TNF-α levels were significantly higher in the unsuccessful treatment group compared to the successful treatment group (10.43±10.17 vs 5.37±5.25, P=0.01) but no differences were observed in IL-10 levels between the study groups. Furthermore, age and sex-adjusted linear regression models showed that non-nucleoside reverse-transcriptase inhibitors (NNRTI)-based treatment regimen is positively associated with serum IL-10 levels in patients with unsuccessful treatment (B coefficient 10.88 (95% CI: 1.32-20.45), P=0.03). Moreover, based on the results of the linear regression models, no relationship between HIV viral load and serum IL-10 and TNF-α level was observed.
|
Conclusion: Results of this study showcased the importance of TNF-α in disease progression and treatment failure. Further future studies regarding this relationship can provide vital information in AIDS treatment research.
|
