Trends in detectable viral load by calendar year in the Australian HIV observational database

Background Recent papers have suggested that expanded combination antiretroviral treatment (cART) through lower viral load may be a strategy to reduce HIV transmission at a population level. We assessed calendar trends in detectable viral load in patients recruited to the Australian HIV Observational Database who were receiving cART. Methods Patients were included in analyses if they had started cART (defined as three or more antiretrovirals) and had at least one viral load assessment after 1 January 1997. We analyzed detectable viral load (>400 copies/ml) in the first and second six months of each calendar year while receiving cART. Repeated measures logistic regression methods were used to account for within and between patient variability. Rates of detectable viral load were predicted allowing for patients lost to follow up. Results Analyses were based on 2439 patients and 31,339 viral load assessments between 1 January 1997 and 31 March 2009. Observed detectable viral load in patients receiving cART declined to 5.3% in the first half of 2009. Predicted detectable viral load based on multivariate models, allowing for patient loss to follow up, also declined over time, but at higher levels, to 13.8% in 2009. Conclusions Predicted detectable viral load in Australian HIV Observational Database patients receiving cART declined over calendar time, albeit at higher levels than observed. However, over this period, HIV diagnoses and estimated HIV incidence increased in Australia

Temporal trends of time to antiretroviral treatment initiation, interruption and modification: examination of patients diagnosed with advanced HIV in Australia.

INTRODUCTION: HIV prevention strategies are moving towards reducing plasma HIV RNA viral load in all HIV-positive persons, including those undiagnosed, treatment naïve, on or off antiretroviral therapy. A proxy population for those undiagnosed are patients that present late to care with advanced HIV. The objectives of this analysis are to examine factors associated with patients presenting with advanced HIV, and establish rates of treatment interruption and modification after initiating ART. METHODS: We deterministically linked records from the Australian HIV Observational Database to the Australian National HIV Registry to obtain information related to HIV diagnosis. Logistic regression was used to identify factors associated with advanced HIV diagnosis. We used survival methods to evaluate rates of ART initiation by diagnosis CD4 count strata and by calendar year of HIV diagnosis. Cox models were used to determine hazard of first ART treatment interruption (duration >30 days) and time to first major ART modification. RESULTS: Factors associated (p<0.05) with increased odds of advanced HIV diagnosis were sex, older age, heterosexual mode of HIV exposure, born overseas and rural-regional care setting. Earlier initiation of ART occurred at higher rates in later periods (2007-2012) in all diagnosis CD4 count groups. We found an 83% (69, 91%) reduction in the hazard of first treatment interruption comparing 2007-2012 versus 1996-2001 (p<0.001), and no difference in ART modification for patients diagnosed with advanced HIV. CONCLUSIONS: Recent HIV diagnoses are initiating therapy earlier in all diagnosis CD4 cell count groups, potentially lowering community viral load compared to earlier time periods. We found a marked reduction in the hazard of first treatment interruption, and found no difference in rates of major modification to ART by HIV presentation status in recent periods