Therapeutic drug monitoring · 2020
Pharmacokinetic Variability During Long-Term Therapeutic Drug Monitoring of Valproate, Clobazam, and Levetiracetam in Patients With Dravet Syndrome.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Johannessen Landmark Cecilie, Heger Katrine, Lund Caroline, Burns Margrete Larsen, Bjørnvold Marit, Sætre Erik, Johannessen Svein I
Аннотация
BACKGROUND: The use of therapeutic drug monitoring (TDM) for antiseizure medications (ASMs) may contribute to treatment optimization in individual patients. This study included patients with Dravet syndrome as they often require close monitoring because of polypharmacy with various ASMs. The aim was to use long-term TDM to investigate pharmacokinetic variability of ASMs in these patients.
METHODS: Retrospective data from patients with Dravet syndrome were collected from the TDM database at the Section for Clinical Pharmacology, National Center for Epilepsy in Norway (2008-2018). Concentration/(dose/kg)ratios (C/D ratios) were calculated for the ASMs and the concentration (C/C ratio) for N-desmethylclobazam. In patients with at least 3 measurements, the CV for C/D ratios for intrapatient and interpatient variability was calculated.
RESULTS: Fifty-three patients (30 male patients/23 female patients) between 2 and 50 years of age (mean, 16 years) were included. Pharmacokinetic variability of the total number of measurements of valproate (n = 417), clobazam and N-desmethylclobazam (n = 328), and levetiracetam (n = 238) was determined. Interpatient variability was more pronounced than intrapatient variability (coefficient of variations: valproate, 65% vs. 24%; levetiracetam, 71% vs. 27%; and clobazam/N-desmethylclobazam, 47%/77% vs. 35%/55%) (P < 0.01). Comedication with stiripentol (n = 16) increased the C/D ratio of valproate by 63% and of clobazam by 133% and the C/C ratio of N-desmethylclobazam/clobazam by 104% (P < 0.05). Younger age also contributed to pharmacokinetic variability.
CONCLUSIONS: Long-term TDM revealed extensive variability in serum concentrations over time; the variability was lowest for levetiracetam, moderate for valproate, and highest for clobazam. Pharmacokinetic variability and interactions can thus be identified and adjusted to facilitate decision making to achieve the optimal treatment outcome.
METHODS: Retrospective data from patients with Dravet syndrome were collected from the TDM database at the Section for Clinical Pharmacology, National Center for Epilepsy in Norway (2008-2018). Concentration/(dose/kg)ratios (C/D ratios) were calculated for the ASMs and the concentration (C/C ratio) for N-desmethylclobazam. In patients with at least 3 measurements, the CV for C/D ratios for intrapatient and interpatient variability was calculated.
RESULTS: Fifty-three patients (30 male patients/23 female patients) between 2 and 50 years of age (mean, 16 years) were included. Pharmacokinetic variability of the total number of measurements of valproate (n = 417), clobazam and N-desmethylclobazam (n = 328), and levetiracetam (n = 238) was determined. Interpatient variability was more pronounced than intrapatient variability (coefficient of variations: valproate, 65% vs. 24%; levetiracetam, 71% vs. 27%; and clobazam/N-desmethylclobazam, 47%/77% vs. 35%/55%) (P < 0.01). Comedication with stiripentol (n = 16) increased the C/D ratio of valproate by 63% and of clobazam by 133% and the C/C ratio of N-desmethylclobazam/clobazam by 104% (P < 0.05). Younger age also contributed to pharmacokinetic variability.
CONCLUSIONS: Long-term TDM revealed extensive variability in serum concentrations over time; the variability was lowest for levetiracetam, moderate for valproate, and highest for clobazam. Pharmacokinetic variability and interactions can thus be identified and adjusted to facilitate decision making to achieve the optimal treatment outcome.