Search

Aims: Aripiprazole is one of the most commonly prescribed antipsychotic drugs to children and adolescents worldwide, but it is associated with serious side-effects, including weight gain. This study assessed the population pharmacokinetics of aripiprazole and its active metabolite and investigated the relationship between pharmacokinetic parameters and body mass index (BMI) in children and adolescents with autism spectrum disorder (ASD) and behavioural problems. Secondary outcomes were metabolic, endocrine, extrapyramidal and cardiac side-effects and drug effectiveness. Methods: Twenty-four children and adolescents (15 males, 9 females) aged 6–18 years were included in a 24-week prospective observational trial. Drug plasma concentrations, side-effects and drug effectiveness were measured at several time points during follow-up. Relevant pharmacokinetic covariates, including CYP2D6, CYP3A4, CYP3A5 and P-glycoprotein (ABCB1) genotypes, were determined. Nonlinear mixed-effects modelling (NONMEM®) was used for a population pharmacokinetic analysis with 92 aripiprazole and 91 dehydro-aripiprazole concentrations. Subsequently, model-based trough concentrations, maximum concentrations and 24-h area under the curves (AUCs) were analysed to predict outcomes using generalized and linear mixed-effects models. Results: For both aripiprazole and dehydro-aripiprazole, one-compartment models best described the measured concentrations, with albumin and BMI as significant covariates. Of all the pharmacokinetic parameters, higher sum (aripiprazole plus dehydro-aripiprazole) trough concentrations best predicted higher BMI z-scores (P <.001) and higher Hb1Ac levels (P =.03) during follow-up. No significant association was found between sum concentrations and effectiveness. Conclusions: Our results indicate a threshold with regard to safety, which suggests that therapeutic drug monitoring of aripiprazole

Aim: Risperidone is the most commonly prescribed antipsychotic drug to children and adolescents worldwide, but it is associated with serious side effects, including weight gain. This study assessed the relationship of risperidone and 9-hydroxyrisperidone trough concentrations, maximum concentrations and 24-hour area under the curves (AUCs) with body mass index (BMI) z-scores in children and adolescents with autism spectrum disorder (ASD) and behavioural problems. Secondary outcomes were metabolic, endocrine, extrapyramidal and cardiac side effects and effectiveness. Methods: Forty-two children and adolescents (32 males) aged 6-18 years were included in a 24-week prospective observational trial. Drug plasma concentrations, side effects and effectiveness were measured at several time points during follow-up. Relevant pharmacokinetic covariates, including medication adherence and CYP2D6, CYP3A4, CYP3A5 and P-glycoprotein (ABCB1) genotypes, were measured. Nonlinear mixed-effects modelling (NONMEM®) was used for a population pharmacokinetic analysis with 205 risperidone and 205 9-hydroxyrisperidone concentrations. Subsequently, model-based trough concentrations, maximum concentrations and 24-hour AUCs were analysed to predict outcomes using generalized and linear mixed-effects models. Results: A risperidone two-compartment model combined with a 9-hydroxyrisperidone one-compartment model best described the measured concentrations. Of all the pharmacokinetic parameters, higher risperidone sum trough concentrations best predicted higher BMI z-scores during follow-up (P <.001). Higher sum trough concentrations also predicted more sedation (P <.05), higher prolactin levels (P <.001) and more effectiveness measured with Aberrant Behavior Checklist irritability score (P <.01). Conclusion: Our results indicate a therapeutic window exists, which suggests that therapeutic drug monitoring of risperidone might increase safety and effectiveness in children and adolesce

In a sample of children aged 8-16 years (N = 151) in a child psychiatric setting, the relationship between VIQ-PIQ discrepancies and both Quality of Life (QoL) and psychosocial problems was explored. It was hypothesized that compared to children without a VIQ-PIQ discrepancy children with a discrepancy would have lower QoL and show more psychosocial problems. Using the WISC-III to measure IQ discrepancies, QoL and the severity of psychosocial problems (measured with the Child Behavior Checklist) were found not to differ between the two groups of children. Neither were there any significant correlations between VIQ-PIQ discrepancies and these mental health indicators. Moreover, the proportion of children showing a VIQ-PIQ discrepancy was found not to deviate from the value in the normal population. The conclusion is that in children with psychiatric problems, VIQ-PIQ differences and core mental health indicators are unrelated and that therefore in diagnostic practice psychologists should be hesitant in assuming such a relationship.