Journal
EPILEPSY & BEHAVIOR
Volume 96, Issue -, Pages 132-140Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.yebeh.2019.04.007
Keywords
Epilepsy; Lamotrigine; Nonadherence; Monte Carlo simulation; Population pharmacokinetics; Remedial dose
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Funding
- National Natural Science Foundation of China [81573505]
- Weak Discipline Construction Project of Shanghai Municipal Commission of Health and Family Planning [2016ZB0301-01]
- Clinical Research Foundation of Zhejiang Medical Association [2017ZYC-A25]
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Objective: This study investigated the effect of delayed or missed doses on the pharmacokinetics (PK) of lamotrigine (LTG) in children with epilepsy and established remedial dosing recommendations for nonadherent patients. Methods: The Monte Carlo simulation based on a published LTG population PK model was used to assess the effect of different scenarios of nonadherence and the subsequently administered remedial regimens. The following three remedial approaches were investigated for each delayed dose: A) A partial dose was administered immediately, and the regular dose was administered at the next scheduled time. B) The delayed dose was administered immediately, followed by a partial dose at the next scheduled time. C) The delayed and partial doses were coadministered immediately, the next scheduled dose was skipped, and the regular dosing was resumed at the subsequent scheduled time. The most appropriate remedial regimen was that with the shortest deviation time from the individual therapeutic window. Results: The effect of nonadherence on PK was dependent on the delay duration and daily dose, and the recommended remedial dose was related to the delay duration and concomitant antiepileptic drugs. Remedial dosing strategies A and B were almost equivalent, whereas C showed a larger PK deviation time. If one dose was missed, double doses were not recommended for the next scheduled time. Conclusions: Simulations provide quantitative insight into the remedial regimens for nonadherent patients, and clinicians should select the optimal regimen based on the status of patients. (C) 2019 Elsevier Inc. All rights reserved.
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