The effect of nonadherence on phenobarbital concentrations and recommendations on the replacement dose using Monte Carlo simulation
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Janthima Methaneethorn
Abstract
Objectives
To determine the impacts of missed phenobarbital (PB) doses on its pharmacokinetics and to investigate the appropriate replacement dosing scheme for various PB missed dose scenarios.
Methods
Monte Carlo simulations were performed using parameters from the selected population pharmacokinetic study. The impacts of missed PB dose and the proper replacement dosing scheme were assessed based on the percent deviation of simulated concentrations outside the reference range from the full adherence scenario.
Results
The impact of missed PB dose on its concentrations depended on the daily dose. The replacement with a respective regular dose and one and a half regular dose was appropriate for the one and two missed doses scenarios for patients receiving PB monotherapy. For patients receiving PB with valproic acid or phenytoin, the same replacement scheme was still appropriate. The results also indicated that weight did not influence the proper replacement dosing scheme.
Conclusions
The impacts of missed PB doses on its pharmacokinetics were identified and the proper replacement dosing schemes for different missed dose scenarios were proposed. These schemes should be implemented based on the clinician’s justification of the patient’s seizure control.
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Research funding: None declared.
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Author contributions: Single author contribution.
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Competing interests: Author states no conflict of interest.
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Informed consent: Not applicable.
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Ethical approval: Not applicable.
References
1. Methaneethorn, J, Leelakanok, N. Pharmacokinetic variability of phenobarbital: a systematic review of population pharmacokinetic analysis. Eur J Clin Pharmacol 2020;77:1–19. https://doi.org/10.1007/s00228-020-03011-x.Suche in Google Scholar PubMed
2. Patsalos, PN, Berry, DJ, Bourgeois, BF, Cloyd, JC, Glauser, TA, Johannessen, SI, et al.. Antiepileptic drugs—best practice guidelines for therapeutic drug monitoring: a position paper by the subcommission on therapeutic drug monitoring, ILAE Commission on Therapeutic Strategies. Epilepsia 2008;49:1239–76. https://doi.org/10.1111/j.1528-1167.2008.01561.x.Suche in Google Scholar PubMed
3. Hvidberg, EF, Dam, M. Clinical pharmacokinetics of anticonvulsants. Clin Pharmacokinet 1976;1:161–88. https://doi.org/10.2165/00003088-197601030-00001.Suche in Google Scholar PubMed
4. Battino, D, Estienne, M, Avanzini, G. Clinical pharmacokinetics of antiepileptic drugs in paediatric patients. Clin Pharmacokinet 1995;29:257–86. https://doi.org/10.2165/00003088-199529040-00005.Suche in Google Scholar PubMed
5. Touw, D, Graafland, O, Cranendonk, A, Vermeulen, R, Van Weissenbruch, M. Clinical pharmacokinetics of phenobarbital in neonates. Eur J Pharmaceut Sci 2000;12:111–6. https://doi.org/10.1016/s0928-0987(00)00145-7.Suche in Google Scholar PubMed
6. Mamiya, K, Hadama, A, Yukawa, E, Ieiri, I, Otsubo, K, Ninomiya, H, et al.. CYP2C19 polymorphism effect on phenobarbitone. Pharmacokineties in Japanese patients with epilepsy: analysis by population pharmacokinetics. Eur J Clin Pharmacol 2000;55:821–5. https://doi.org/10.1007/s002280050703.Suche in Google Scholar PubMed
7. Goto, S, Seo, T, Murata, T, Nakada, N, Ueda, N, Ishitsu, T, et al.. Population estimation of the effects of cytochrome P450 2C9 and 2C19 polymorphisms on phenobarbital clearance in Japanese. Ther Drug Monit 2007;29:118–21. https://doi.org/10.1097/ftd.0b013e318030def0.Suche in Google Scholar
8. Šíma, M, Michaličková, D, Slanař, O. What is the best predictor of phenobarbital pharmacokinetics to use for initial dosing in neonates? Pharmaceutics 2021;13:301. https://doi.org/10.3390/pharmaceutics13030301.Suche in Google Scholar PubMed PubMed Central
9. Murphy, JE. Clinical pharmacokinetics, 5th ed. Bethesda: American Society of Health-System Pharmacists, Inc; 2011:263–72 pp.Suche in Google Scholar
10. Das, AM, Ramamoorthy, L, Narayan, SK, Wadvekar, V, Harichandrakumar, K. Adherence to antiepileptic regime: a cross-sectional survey. Neurol India 2020;68:856. https://doi.org/10.4103/0028-3886.293468.Suche in Google Scholar PubMed
11. Davis, KL, Candrilli, SD, Edin, HM. Prevalence and cost of nonadherence with antiepileptic drugs in an adult managed care population. Epilepsia 2008;49:446–54. https://doi.org/10.1111/j.1528-1167.2007.01414.x.Suche in Google Scholar PubMed
12. Getnet, A, Woldeyohannes, SM, Bekana, L, Mekonen, T, Fekadu, W, Menberu, M, et al.. Antiepileptic drug nonadherence and its predictors among people with epilepsy. Behav Neurol 2016;2016:3189108. https://doi.org/10.1155/2016/3189108.Suche in Google Scholar PubMed PubMed Central
13. Ogboi Sonny, J, Babajide, F, Ademola, OA, Olabunmi, O, Agu, PU. Evaluation of factors influencing medication adherence in patients with epilepsy in rural communities of Kaduna State, Nigeria. Neurosci Med 2011;2:299–305. https://doi.org/10.4236/nm.2011.24039.Suche in Google Scholar
14. Samsonsen, C, Reimers, A, Bråthen, G, Helde, G, Brodtkorb, E. Nonadherence to treatment causing acute hospitalizations in people with epilepsy: an observational, prospective study. Epilepsia 2014;55:e125–8. https://doi.org/10.1111/epi.12801.Suche in Google Scholar PubMed
15. Phenobarbital. Prescribing information. Montréal: Pendopharm, Division of Pharmascience Inc. Phenobarbital tablets [prescribing information]; 2018.Suche in Google Scholar
16. Gu, J-Q, Guo, Y-P, Jiao, Z, Ding, J-J, Li, G-F. How to handle delayed or missed doses: a population pharmacokinetic perspective. Eur J Drug Metab Pharmacokinet 2020;45:163–72. https://doi.org/10.1007/s13318-019-00598-0.Suche in Google Scholar PubMed
17. Yu, E-Q, Jiao, Z, Wang, C-Y, Ding, J-J, Zhang, X-H. Remedial dosing recommendations for delayed or missed doses of lamotrigine in pediatric patients with epilepsy using Monte Carlo simulations. Epilepsy Behav 2019;96:132–40. https://doi.org/10.1016/j.yebeh.2019.04.007.Suche in Google Scholar PubMed
18. Belayneh, Z, Mekuriaw, B. A systematic review and meta-analysis of anti-epileptic medication non-adherence among people with epilepsy in Ethiopia. Arch Publ Health 2020;78:23. https://doi.org/10.1186/s13690-020-00405-2.Suche in Google Scholar PubMed PubMed Central
19. Ejeliogu, E, Courage, A. Prevalence and factors associated with non-adherence to antiepileptic drugs among children with epilepsy in Jos, Nigeria. Niger J Paediatr 2020;47:240–5. https://doi.org/10.4314/njp.v47i3.8.Suche in Google Scholar
20. Ding, J-J, Zhang, Y-J, Jiao, Z, Wang, Y. The effect of poor compliance on the pharmacokinetics of carbamazepine and its epoxide metabolite using Monte Carlo simulation. Acta Pharmacol Sin 2012;33:1431–40. https://doi.org/10.1038/aps.2012.135.Suche in Google Scholar PubMed PubMed Central
21. Wang, C-Y, Jiao, Z, Ding, J-J, Yu, E-Q, Zhu, G-X. Remedial dosing recommendations for delayed or missed doses of valproic acid in patients with epilepsy based on Monte Carlo simulations. Epilepsy Behav 2020;111:107265. https://doi.org/10.1016/j.yebeh.2020.107265.Suche in Google Scholar PubMed
22. Díaz, RAS, Sancho, J, Serratosa, J. Antiepileptic drug interactions. Neurol 2008;14:S55–65. https://doi.org/10.1097/01.nrl.0000340792.61037.40.Suche in Google Scholar PubMed
23. Kuranari, M, Tatsukawa, H, Seike, M, Saikawa, T, Ashikari, Y, Kodama, Y, et al.. Effect of phenytoin on phenobarbital pharmacokinetics in a patient with epilepsy. Ann Pharmacother 1995;29:83–4. https://doi.org/10.1177/106002809502900118.Suche in Google Scholar PubMed
24. Methaneethorn, J, Panomvana, D, Vachirayonstien, T. Preliminary study of the association between the elimination parameters of phenytoin and phenobarbital. Drug Metab Pers Ther 2017;32:151–6. https://doi.org/10.1515/dmpt-2017-0017.Suche in Google Scholar PubMed
© 2022 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Review
- Impact of environmental toxicants exposure on gut-brain axis in Parkinson disease
- Original Articles
- The effect of nonadherence on phenobarbital concentrations and recommendations on the replacement dose using Monte Carlo simulation
- SLCO1B1 c.521T>C gene polymorphism decreases hypoglycemia risk in sulfonylurea-treated type 2 diabetic patients
- Association of VKORC1 and CYP2C9 single-nucleotide polymorphisms with warfarin dose adjustment in Saudi patients
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- No association between LDL receptor and CETP genetic variants and atorvastatin response in Jordanian hyperlipidemic patients
- Type 2 diabetes: an exploratory genetic association analysis of selected metabolizing enzymes and transporters and effects on cardiovascular and renal biomarkers
- Potential factors of Helicobacter pylori resistance to clarithromycin
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Artikel in diesem Heft
- Frontmatter
- Review
- Impact of environmental toxicants exposure on gut-brain axis in Parkinson disease
- Original Articles
- The effect of nonadherence on phenobarbital concentrations and recommendations on the replacement dose using Monte Carlo simulation
- SLCO1B1 c.521T>C gene polymorphism decreases hypoglycemia risk in sulfonylurea-treated type 2 diabetic patients
- Association of VKORC1 and CYP2C9 single-nucleotide polymorphisms with warfarin dose adjustment in Saudi patients
- Effect of CYP2C9, PTGS-1 and PTGS-2 gene polymorphisms on the efficiency and safety of postoperative analgesia with ketoprofen
- No association between LDL receptor and CETP genetic variants and atorvastatin response in Jordanian hyperlipidemic patients
- Type 2 diabetes: an exploratory genetic association analysis of selected metabolizing enzymes and transporters and effects on cardiovascular and renal biomarkers
- Potential factors of Helicobacter pylori resistance to clarithromycin
- Letter to the Editor
- Phenylalanine monooxygenase and the ‘sulfoxidation polymorphism’; the salient points
