A Statistical Model to Predict the Development of HIV Drug Resistance in Drug-naïve Individuals Incorporating the Effects of Boosted PI Regimens and Adherence
Vikram Gill*, P Harrigan, R Hogg, and V Lima
BC Ctr for Excellence in HIV/AIDS, Vancouver, Canada
previously characterized HIV resistance development in a large population-based
cohort of individuals (HOMER) starting their first HAART regimen by systematic
genotyping. Here we describe a statistical model to predict the emergence of
resistance, adjusting for the simultaneous effects of adherence, baseline
plasma viral load, and initial treatment regimen.
Methods: Logistic regression
was used to create a statistical model of HIV drug resistance for drug-naive
patients initiating HAART between August 1996 and November 2005 (n = 1975, incorporating 5137 resistance
tests). The model included 818 individuals
initiating non-boosted protease inhibitor (PI) regimens, 353 initiating boosted PI regimens, and 804 initiating non-nucleoside reverse transcriptase
inhibitor (NNRTI) -based regimens. Several baseline predictors were
incorporated in the model, including baseline plasma viral
load, CD4 cell count, age, gender, history of injection drug use, and
adherence estimated by prescription refill.
Results: Of the total, 539 individuals (27%) developed resistance during a median of 4.6 years of follow-up (interquartile range 2.5 to 7.2).
The model predicted no difference in the odds of developing key resistance
mutations between non-boosted PI regimens (reference group) and NNRTI-based
HAART regimens (odds ratio [OR] = 0.86, 95% confidence interval (CI) 0.68 to 1.08),
but greatly reduced odds for PI-boosted regimens (OR = 0.23, 95%CI 0.16 to 0.34).
A skewed, non-linear relationship with adherence was confirmed, as was a strong
association of resistance with increasing plasma viral load
and a weaker association with decreasing CD4 cell count and a history of
injection drug use. Of particular interest, the dependence of resistance
selection on baseline plasma viral load and on
patient adherence was markedly decreased for boosted PI regimens; for example,
the estimated probability of resistance at the worst
adherence strata for boosted PI was equal to or lower than that observed
at any adherence strata for unboosted
PI or NNRTI regimens.
Conclusions: The statistical
model closely reflected the previously presented systematic characterization.
In a “real world” population of individuals initiating first HAART, individuals
starting on a boosted PI regimen had a 5-fold lower odds ratio of developing
HIV drug resistance. Furthermore, the model shows that the relationship between
resistance and adherence (as well as resistance and plasma
viral load) is less strong for individuals initiating boosted PI
regimens than it is for those starting non-boosted PI or NNRTI-based regimens.