The effect of malnutrition on the pharmacokinetics and virologic outcomes of lopinavir, efavirenz and nevirapine in food insecure HIV-infected children in Tororo, Uganda

Abstract

Background: Malnutrition may impact the pharmacokinetics (PKs) of antiretroviral medications and virologic responses in HIV-infected children. The authors therefore evaluated the PK of nevirapine (NVP), efavirenz (EFV) and lopinavir (LPV) in associations with nutritional status in a cohort of HIV-infected Ugandan children.

Methods: Sparse dried blood spot samples from Ugandan children were used to estimate plasma concentrations. Historical PK data from children from 3 resource-rich countries (RRC) were utilized to develop the PK models.

Results: Concentrations in 330 dried blood spot from 163 Ugandan children aged 0.7-7 years were analyzed in reference to plasma PK data (1189 samples) from 204 children from RRC aged 0.5-12 years. Among Ugandan children, 48% was malnourished (underweight, thin or stunted). Compared to RRC, Ugandan children exhibited reduced bioavailability of EFV and LPV; 11% (P=0.045) and 18% (P=0.008), respectively. In contrast, NVP bioavailability was 46% higher in Ugandan children (P<0.001) with a trend toward greater bioavailability when malnourished. Children receiving LPV, EFV or NVP had comparable risk of virologic failure. Among children on NVP, low height and weight for age Z scores were associated with reduced risk of virologic failure (P=0.034, P=0.068, respectively).

Conclusions: Ugandan children demonstrated lower EFV and LPV and higher NVP exposure compared to children in RRC, perhaps reflecting the consequence of malnutrition on bioavailability. In children receiving NVP, the relation between exposure, malnutrition and outcome turned out to be marginally significant. Further investigations are warranted using more intensive PK measurements and adequate adherence assessments, to further assess causes of virologic failure in Ugandan children.

Figures

Figure 1

Simulated concentration-time profiles* in children from the RRC datasets (right) and Ugandan children (left) using a) EFV, b) LPV, c) NVP. * Simulations were performed using prediction corrected visual predictive checks. Concentrations were predicted validated literate-based models for EFV, LPV and NVP. A visual predictive check compares the observations and simulated predictions and can be used to assess ability of the validated PK-models to reproduce the central tendency and the variability in the observed Ugandan data. correction is performed by normalizing the observed and simulated dependent variable within a single bin (clustered data) based on the typical population prediction for the median independent variable (eg. The individual clearance for a patient of 18 kg, is normalized to the population predicted clearance of a patient of that weight). The solid lines represent the 5th percentile, median and 95th percentile of the prediction corrected observed plasma concentrations. The semitransparent dark grey field represents a simulation-based 95% confidence interval for the median and the semitransparent light grey fields show the 95% confidence intervals of the simulated data. EFV: efavirenz, LPV: lopinavir, NVP: nevirapine,

Figure 1

Simulated concentration-time profiles* in children from the RRC datasets (right) and Ugandan children (left) using a) EFV, b) LPV, c) NVP. * Simulations were performed using prediction corrected visual predictive checks. Concentrations were predicted validated literate-based models for EFV, LPV and NVP. A visual predictive check compares the observations and simulated predictions and can be used to assess ability of the validated PK-models to reproduce the central tendency and the variability in the observed Ugandan data. correction is performed by normalizing the observed and simulated dependent variable within a single bin (clustered data) based on the typical population prediction for the median independent variable (eg. The individual clearance for a patient of 18 kg, is normalized to the population predicted clearance of a patient of that weight). The solid lines represent the 5th percentile, median and 95th percentile of the prediction corrected observed plasma concentrations. The semitransparent dark grey field represents a simulation-based 95% confidence interval for the median and the semitransparent light grey fields show the 95% confidence intervals of the simulated data. EFV: efavirenz, LPV: lopinavir, NVP: nevirapine,

Figure 1

Simulated concentration-time profiles* in children from the RRC datasets (right) and Ugandan children (left) using a) EFV, b) LPV, c) NVP. * Simulations were performed using prediction corrected visual predictive checks. Concentrations were predicted validated literate-based models for EFV, LPV and NVP. A visual predictive check compares the observations and simulated predictions and can be used to assess ability of the validated PK-models to reproduce the central tendency and the variability in the observed Ugandan data. correction is performed by normalizing the observed and simulated dependent variable within a single bin (clustered data) based on the typical population prediction for the median independent variable (eg. The individual clearance for a patient of 18 kg, is normalized to the population predicted clearance of a patient of that weight). The solid lines represent the 5th percentile, median and 95th percentile of the prediction corrected observed plasma concentrations. The semitransparent dark grey field represents a simulation-based 95% confidence interval for the median and the semitransparent light grey fields show the 95% confidence intervals of the simulated data. EFV: efavirenz, LPV: lopinavir, NVP: nevirapine,