Archive \ Volume.10 2019 Issue 2

Prospective Evaluation of p24 Antigen and HIV-1 Protease Assays at 6 Months and 12 Months Initiation of Antiretroviral Therapy in HIV Infected Participants at Federal Medical Center, Lokoja, Nigeria

Isaac P Emeje , Charles C Onyenekwe , Nkiruka R Ukibe , Joseph E Ahaneku

Background: This was a cross-sectional study designed to evaluate the potential use of p24 antigen and HIV-1 protease assays in treatment monitoring of HIV-1 infection at Federal Medical Center, Lokoja Nigeria. Materials and Methods: 154 participants aged 18-64 years were randomly recruited. 40 (group A) participants on efavirenz, Lamivudine, and tenofovir, 35 (group B) participants on nevirapine, lamivudine, and zidovudine served as a test, while 79 (group C) participants not antiretroviral therapy (ART) served as control. Results: P24 antigen, HIV-1 protease and viral load were significantly decreased in test participants than in control participants (f=14.59, p=0.002), (f=22.9, p=0.005) and (f=117.541, p=0.001 respectively). Antigenic markers in test participants with 6 months of therapy were significantly higher than 12 months of therapy (P<0.05). Plasma levels of tenofovir, lamivudine, and efavirenz in test participants were significantly lower while nevirapine was significantly higher at 6 months than in 12 months of therapy (P<0.05 respectively). Strong positive correlations were observed between p24 antigen, HIV-1 protease, and viral load while negative correlations were observed between p24 antigen, protease, viral load, and CD4+ t-cell counts, then between lamivudine, nevirapine, tenofovir and viral load. Conclusions: Decreased p24 antigen and HIV-1 protease with undetectable viral load in HIV infected participants indicated successful suppression of HIV viremia and strongly suggests good antigenic markers for treatment monitoring in resource-poor settings where regular viral load monitoring is unavailable. A combination of HIV-1 protease enzyme and p24 antigen assays with viral load and possibly CD4+ count can serve as tools for identifying participants with clinically insignificant symptoms of treatment failure.