Effects of miglustat therapy on neurological disorder and survival in early-infantile Niemann-Pick disease type C: a national French retrospective study

Abstract Background Niemann-Pick disease type C (NP-C) is a rare neurovisceral lysosomal lipid storage disease characterized by progressive neurodegeneration and premature death. While miglustat can stabilize neurological manifestations in later onset forms of NP-C, its efficacy in the early-infantile neurological form has not been demonstrated. In this observational retrospective study, we compared long-term neurodevelopmental outcome and survival between an untreated and a treated group of early infantile NP-C patients. Methods Data available on all NP-C patients with early infantile neurological onset diagnosed in France between 1990 and 2013 were compiled. Patients with incomplete data or who had died from a systemic perinatal, rapidly fatal form were excluded. Results Ten patients were included in the treated group (year of birth: 2006–2012), and 16 patients in the untreated group [born 1987–2005 (n = 15), 2012 (n = 1)]. The median age at neurological onset was 9 months (5–18) in the treated group, and 12 months (3–18) in the untreated group (p = 0.22). Miglustat therapy was started at a median age of 24.5 months (9–29) and median duration was 30 months (11–56). Gastrointestinal adverse events were reported in 7/10 patients on miglustat. All patients developed loss of psychomotor acquisitions or additional neurological symptoms despite miglustat therapy. The ages of developmental milestones and neurological involvement did not significantly differ between the two groups. Four patients in the untreated group were lost to follow up. The 22 remaining patients had died by the end of the study and no patient survived beyond the age of 7.4 years. The median survival age was 4.42 years in the untreated group and 5.56 years in the treated group; the Kaplan–Meier survival curves were not significantly different (log-rank test: p = 0.11). Conclusions Miglustat allowed no significant long-term neurodevelopmental improvement nor significant increase of survival in patients with early infantile NP-C

Predictive Performance of Population Pharmacokinetic Models of Levetiracetam in Children and Evaluation of Dosing Regimen

International audienceLevetiracetam is a broad-spectrum antiepileptic drug that exhibits high interindividual variability in serum concentrations in children. A population pharmacokinetic approach can be used to explain this variability and optimize dosing schemes. The objectives are to identify the best predictive population pharmacokinetic model for children and to evaluate recommended doses using simulations and Bayesian forecasting. A validation cohort included children treated with levetiracetam who had a serum drug concentration assayed during therapeutic drug monitoring. We assessed the predictive performance of all the population pharmacokinetic models published in the literature using mean prediction errors, root mean squared errors, and visual predictive checks. A population model was finally constructed on the data, and dose simulations were performed to evaluate doses. We included 267 levetiracetam concentrations ranging from 2 to 69 mg/L from 194 children in the validation cohort. Six published models were externally evaluated. Most of the models underestimated the variability of our population. A 1-compartment model with first-order absorption and elimination with allometric scaling was finally fitted on our data. In our cohort, 57% of patients had a trough concentration 5 mg/L, doses ≥30 mg/kg/d for patients ≤50 kg and ≥2000 mg/d for patients >50 kg are required. In our population, a high percentage of children had low trough concentrations. Our population pharmacokinetic model could be used for therapeutic drug monitoring of levetiracetam in children