Modeling trend of the immune system in HIV positive people treated with antiretroviral drugs, using Markov model

After primary infection, the number of CD4 T-cells decreases with disease progress. The patient’s immunological status could inform by The CD4 T-cell counts over the time. The main purpose of this study is to assess the trend of CD4 cell count in HIV+ patient that received Antiretroviral Therapy (ART) by using a multistate Markov model to estimate transition intensities and transition probabilities among various states. A total of 122 HIV+ patients were included in this cohort study who are undergoing Antiretroviral Therapy treatment in the Iran AIDS center in Imam Khomeini Hospital in Tehran that inter during March 1995 to January 2005 and then fallow up to October 2014. All adults with at least two follow-up visits in addition to their pre-ART treatment were considered to be eligible for inclusion in the study. Continuous-time Markov processes are used to describe the evolution of a disease over different states. The mean sojourn time for each state was estimated by multi state Markov model. Sample included 22 (18%) female with a mean age of 43.32 (standard deviation 8.33) years and 100 (82%) male with a mean age of 45.28 (standard deviation 8.34) year. Age was divided in to two categories, 40 years old and lower than that 66 (54.1) patents and persons older than 40 years old 56 (45.9) patents. A total of 122 patients were included. 29 patients died during follow-up. One year transition probability for staying in state 1 of CD4 cell count was 51%. This probability for six year was 33%. The mean sojourn time for sate 4 was 21 month. The hazard ratio of transition from state 3 to state 4 was 4.4 in men related to women. The use of antiretroviral therapy in the treatment of HIV infected persons reduce viral replication and increase in CD4 T lymphocyte count, and delay the progression of disease. This paper is shown the progression of this trend.