Age-specific safety of pharmacotherapy for behavioral disorders in children and adolescents: a retrospective study

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

Background: Behavioral disorders occur in 1–11% of children and adolescents. Antipsychotics, which are unsafe medications, are often used for behavioral disorders. There are studies that demonstrate different rates of adverse drug reactions (ADRs) among children under 13 years of age or older. This emphasizes the need for separate analysis of children and adolescents when assessing risk factors for ADRs to pharmacotherapy.

Objective: Determination of clinical and demographic risk factors for ADRs to pharmacotherapy for behavioral disorders with separate analysis for children and adolescents.

Materials and methods: The study included 300 case histories of children and adolescents hospitalized in an acute psychiatric hospital for behavioral disorders. The sample was divided into 150 patients aged 12 years or younger (subgroup «Children») and 150 aged 13 years and older (subgroup «Adolescents»). All patients received an antipsychotic as their primary therapy. Using the global trigger method, each case history was searched for ADRs. Data on the pharmacotherapy taken were extracted, potentially dangerous drug interactions were recorded, and the Medical appropriateness index and Anticholinergic scale score were calculated. Risk factors for the development of ADRs were assessed using nonparametric statistics and logistic regression analysis.

Results: 57 ADRs were detected among patients (28 in the Children subgroup, 29 in the Adolescents subgroup). Most often, ADRs were detected in patients aged 11 to 15 years. The subgroups of children and adolescents differed significantly in the maximum dose of the second prescribed antipsychotic (higher in adolescents: 60 [37.5; 108] versus 45 [25; 72] mg/day, p=0.019), the number of hospitalizations over the past 12 months (children – 1 [1; 2], adolescents – 1 [1; 1]; p=0.005). Logistic regression identified significant risk factors for the development of ADRs: 1) for the entire sample «Duplicate antipsychotics» (OR=2.505; 95% CI: 1.308–4.798; p = 0.006), high body mass index (OR=0.915; 95% CI: 0.845–0.991; p = 0.029); 2) for the subgroup «Adolescents» – «Duplicate antipsychotics» (OR=2.461; 95% CI: 1.072–5.65; p = 0.034); 3) for the subgroup «Children» no significant risk factors for the development of ADRs were identified.

Conclusion: ADRs to antipsychotics in children and adolescents with behavioral disorders depend on the rationality of pharmacotherapy. Duplicate antipsychotics is a significant risk factor for the development of ADRs. The risk of developing ADRs in patients under 13 years of age is less dependent on the parameters of pharmacotherapy (antipsychotic dosage, duplication of antipsychotics). This study indicates the need for a detailed study of risk factors for ADRs depending on the child’s age.

Full Text

Restricted Access

About the authors

D. V. Ivaschenko

Russian Medical Academy of Continuous Professional Education

Email: aysinf@yandex.ru
ORCID iD: 0000-0002-2295-7167

Dr. Sci. (Med.), Associate Professor, Head of the Department of Child Psychiatry and Psychotherapy

Russian Federation, Moscow

F. R. Aysin

G.E. Sukhareva Scientific and Practical Center for Mental Health of Children and Adolescents

Email: aysinf@yandex.ru
ORCID iD: 0000-0003-1145-1600
SPIN-code: 3573-6558

Clinical Pharmacologist

Russian Federation, Moscow

P. A. Bialkovskaia

Russian Medical Academy of Continuous Professional Education

Author for correspondence.
Email: aysinf@yandex.ru
ORCID iD: 0009-0003-0664-6953

Senior Laboratory Assistant, Department of Child Psychiatry and Psychotherapy

Russian Federation, Moscow

B. R. Gragyants

Pirogov Russian National Research Medical University

Email: aysinf@yandex.ru
ORCID iD: 0009-0007-4074-3983

Student

Russian Federation, Moscow

Yu. S. Shevchenko

Russian Medical Academy of Continuous Professional Education

Email: aysinf@yandex.ru
ORCID iD: 0000-0001-9871-8704

Dr. Sci. (Med.)

Russian Federation, Moscow

D. A. Sychev

Russian Medical Academy of Continuous Professional Education

Email: aysinf@yandex.ru
ORCID iD: 0000-0002-4496-3680

Dr. Sci. (Med.), Professor, Professor of the Russian Academy of Sciences, Academician of the Russian Academy of Sciences, Head of the Department of Clinical Pharmacology and Therapy named after B.E. Votchal, Russian Medical Academy of Continuous Professional Education; Scientific Director of the Center for World-Class Genomic Research «Center for Predictive Genetics, Pharmacogenetics and Personalized Therapy», Petrovsky National Research Centre of Surgery

Russian Federation, Moscow

References

  1. Pingault J.B., Cote S.M., Galera C., et al. Childhood trajectories of inattention, hyperactivity and oppositional behaviors and prediction of substance abuse/dependence: a 15-year longitudinal population-based study. Mol Psychiatry. 2013;18(7):806–812. https://dx.doi.org/10.1038/mp.2012.87
  2. The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM–5; American Psychiatric Association, 2013).
  3. International Classification of Diseases, 11-th Revision (ICD-10; WHO, 2019).
  4. Canino G., Polanczyk G., Bauermeister J.J., et al. Does the prevalence of CD and ODD vary across cultures? Soc Psychiatry Psychiatr Epidemiol. 2010;45(7):695–704. https://dx.doi.org/10.1007/s00127-010-0242-y
  5. Pringsheim T., Hirsch L., Gardner D., et al. The pharmacological management of oppositional behaviour, conduct problems, and aggression in children and adolescents with attention-deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder: a systematic review and meta-analysis. Part 2: antipsychotics and traditional mood stabilizers. Can J Psychiatry. 2015;60(2):52–61. https://dx.doi.org/10.1177/070674371506000203
  6. Loy J.H., Merry S.N., Hetrick S.E., et al. Atypical antipsychotics for disruptive behaviour disorders in children and youths. Cochrane Database Syst Rev. 2017;8(8):CD008559. https://dx.doi.org/10.1002/14651858.CD008559.pub3
  7. Shafiq S., Pringsheim T. Using antipsychotics for behavioral problems in children. Expert Opin Pharmacother. 2018;19(13):1475–1488. https://dx.doi.org/10.1080/14656566.2018.1509069
  8. Solmi M., Murru A., Pacchiarotti I., et al. Safety, tolerability, and risks associated with first- and second-generation antipsychotics: a state-of-the-art clinical review. Ther Clin Risk Manag. 2017;13:757–777. https://dx.doi.org/10.2147/TCRM.S117321
  9. van den Anker J., Reed M.D., Allegaert K., Kearns G.L. Developmental Changes in Pharmacokinetics and Pharmacodynamics. J Clin Pharmacol. 2018;58 Suppl 10:S10–S25. https://dx.doi.org/10.1002/jcph.1284
  10. Johnson T.N., Rostami-Hodjegan A., Tucker G.T. Prediction of the clearance of eleven drugs and associated variability in neonates, infants and children. Clin Pharmacokinet. 2006;45(9):931–956. https://dx.doi.org/10.2165/00003088-200645090-00005
  11. Kearns G.L., Abdel-Rahman S.M., Alander S.W., et al. Developmental pharmacology-drug disposition, action, and therapy in infants and children. N Engl J Med. 2003;349(12):1157–1167. https://dx.doi.org/10.1056/NEJMra035092
  12. Holford N. Dosing in children. Clin Pharmacol Ther. 2010;87(3):367–370. https://dx.doi.org/10.1038/clpt.2009.262
  13. Thiesen S., Conroy E.J., Bellis J.R., et al. Incidence, characteristics and risk factors of adverse drug reactions in hospitalized children - a prospective observational cohort study of 6,601 admissions. BMC Med. 2013;11:237. https://dx.doi.org/10.1186/1741-7015-11-237
  14. Ji H.H., Song L., Xiao J.W., et al. Adverse drug events in Chinese pediatric inpatients and associated risk factors: a retrospective review using the Global Trigger Tool. Sci Rep. 2018;8(1):2573. https://dx.doi.org/10.1038/s41598-018-20868-2
  15. Bouquet E., Star K., Jonville-Btra A.P., et al. Pharmacovigilance in pediatrics. Therapie. 2018;73(2):171–180. https://dx.doi.org/10.1016/j.therap.2017.11.012
  16. Medhekar R., Aparasu R., Bhatara V., et al. Risk factors of psychotropic polypharmacy in the treatment of children and adolescents with psychiatric disorders. Res Social Adm Pharm. 2019;15(4):395–403. https://dx.doi.org/10.1016/j.sapharm.2018.06.005
  17. Chen J., Wall M. Epidemiology and risk factors for idiopathic intracranial hypertension. Int Ophthalmol Clin. 2014;54(1):1–11. https://dx.doi.org/10.1097/IIO.0b013e3182aabf11
  18. Aldea Perona A., Garcia-Sáiz M., Sanz Álvarez E. Psychiatric disorders and montelukast in children: a disproportionality analysis of the VigiBase(®). Drug Saf. 2016;39(1):69–78. https://dx.doi.org/10.1007/s40264-015-0360-2
  19. Leucht S., Chaimani A., Krause M., et al. The response of subgroups of patients with schizophrenia to different antipsychotic drugs: a systematic review and meta-analysis. Lancet Psychiatry. 2022;9(11):884–893. https://dx.doi.org/10.1016/S2215-0366(22)00304-2
  20. Chung Y.S., Shao S.C., Chi M.H., et al. Comparative cardiometabolic risk of antipsychotics in children, adolescents and young adults. Eur Child Adolesc Psychiatry. 2021;30(5):769–783. https://dx.doi.org/10.1007/s00787-020-01560-1
  21. Rashed A.N., Wong I.C., Cranswick N., et al. Risk factors associated with adverse drug reactions in hospitalised children: international multicentre study. Eur J Clin Pharmacol. 2012;68(5):801–810. https://dx.doi.org/10.1007/s00228-011-1183-4
  22. T’jollyn H., Snoeys J., Vermeulen A., et al. Physiologically based pharmacokinetic predictions of tramadol exposure throughout pediatric life: an analysis of the different clearance contributors with emphasis on CYP2D6 maturation. AAPS J. 2015;17(6):1376–1387. https://dx.doi.org/10.1208/s12248-015-9803-z
  23. Taurines R., Kunkel G., Fekete S., et al. Serum concentration-dose relationship and modulation factors in children and Aaolescents treated with fluvoxamine. Pharmaceutics. 2024;16(6):772. https://dx.doi.org/10.3390/pharmaceutics16060772
  24. Sajith S.G., Fung D.S.S., Chua H.C. The Mental Health Trigger Tool: development and testing of a specialized Trigger Tool for Mental Health Settings. J Patient Saf. 2021;17(4):e360–e366. https://dx.doi.org/10.1097/PTS.0000000000000606
  25. Gardner D.M., Murphy A.L., O’Donnell H., et al. International consensus study of antipsychotic dosing. Am J Psychiatry. 2010;167(6):686–693. https://dx.doi.org/10.1176/appi.ajp.2009.09060802
  26. Samsa G.P., Hanlon J.T., Schmader K.E., et al. A summated score for the medication appropriateness index: development and assessment of clinimetric properties including content validity. J Clin Epidemiol. 1994;47(8):891–896. https://dx.doi.org/10.1016/0895-4356(94)90192-9
  27. Ramos H., Moreno L., Pérez-Tur J., et al. CRIDECO Anticholinergic Load Scale: an updated Anticholinergic Burden Scale. Comparison with the ACB Scale in Spanish individuals with subjective memory complaints. J Pers Med. 2022;12(2):207. https://dx.doi.org/10.3390/jpm12020207
  28. Salahudeen M.S., Duffull S.B., Nishtala P.S. Anticholinergic burden quantified by anticholinergic risk scales and adverse outcomes in older people: a systematic review. BMC Geriatr. 2015;15:31. https://dx.doi.org/10.1186/s12877-015-0029-9
  29. Valkonen V., Haatainen K., Saano S., et al. Evaluation of Global trigger tool as a medication safety tool for adverse drug event detection-a cross-sectional study in a tertiary hospital. Eur J Clin Pharmacol. 2023;79(5):617–625. https://dx.doi.org/10.1007/s00228-023-03469-5

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Figure 1. Distribution of adverse reaction frequency by age

Download (67KB)
Indexing metadata
3. Figure 2. Antipsychotic dosing i n children and adolescents stratified by adverse reaction status

Download (98KB)
Indexing metadata
4. Figure 3. Combinations of antipsychotic medications observed in the study population

Download (118KB)
Indexing metadata

Copyright (c) 2025 Bionika Media