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Comparative Study
. 2024 Jul;8(7):510-521.
doi: 10.1016/S2352-4642(24)00098-1.

Comparative physiological effects of antipsychotic drugs in children and young people: a network meta-analysis

Affiliations
Comparative Study

Comparative physiological effects of antipsychotic drugs in children and young people: a network meta-analysis

Maria Rogdaki et al. Lancet Child Adolesc Health. 2024 Jul.

Abstract

Background: The degree of physiological responses to individual antipsychotic drugs is unclear in children and adolescents. With network meta-analysis, we aimed to investigate the effects of various antipsychotic medications on physiological variables in children and adolescents with neuropsychiatric and neurodevelopmental conditions.

Methods: For this network meta-analysis, we searched Medline, EMBASE, PsycINFO, Web of Science, and Scopus from database inception until Dec 22, 2023, and included randomised controlled trials comparing antipsychotics with placebo in children or adolescents younger than 18 years with any neuropsychiatric and neurodevelopmental condition. Primary outcomes were mean change from baseline to end of acute treatment in bodyweight, BMI, fasting glucose, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, prolactin, heart rate, systolic blood pressure (SBP), and QT interval corrected for heart rate (QTc) for patients receiving either active treatment or placebo. For multigroup trials reporting several doses, we calculated a summary value for each physiological variable for all doses. After transitivity assessment, we fitted frequentist random-effects network meta-analyses for all comparisons in the network. A Kilim plot was used to summarise the results for all treatments and outcomes, providing information regarding the strength of the statistical evidence of treatment effects, using p values. Network heterogeneity was assessed with τ, risk of bias of individual trials was assessed with the Cochrane Collaboration's Tool for Assessing Risk of Bias, and the credibility of findings from each network meta-analysis was assessed with the Confidence in Network Meta-Analysis (CINEMA) app. This study is registered on PROSPERO (CRD42021274393).

Findings: Of 6676 studies screened, 47 randomised controlled trials were included, which included 6500 children (mean age 13·29 years, SD 2·14) who received treatment for a median of 7 weeks (IQR 6-8) with either placebo (n=2134) or one of aripiprazole, asenapine, blonanserin, clozapine, haloperidol, lurasidone, molindone, olanzapine, paliperidone, pimozide, quetiapine, risperidone, or ziprasidone (n=4366). Mean differences for bodyweight change gain compared with placebo ranged from -2·00 kg (95% CI -3·61 to -0·39) with molindone to 5·60 kg (0·27 to 10·94) with haloperidol; BMI -0·70 kg/m2 (-1·21 to -0·19) with molindone to 2·03 kg/m2 (0·51 to 3·55) with quetiapine; total cholesterol -0·04 mmol/L (-0·39 to 0·31) with blonanserin to 0·35 mmol/L (0·17 to 0·53) with quetiapine; LDL cholesterol -0·12 mmol/L (-0·31 to 0·07) with risperidone or paliperidone to 0·17 mmol/L (-0·06 to 0·40) with olanzapine; HDL cholesterol 0·05 mmol/L (-0·19 to 0·30) with quetiapine to 0·48 mmol/L (0·18 to 0·78) with risperidone or paliperidone; triglycerides -0·03 mmol/L (-0·12 to 0·06) with lurasidone to 0·29 mmol/L (0·14 to 0·44) with olanzapine; fasting glucose from -0·09 mmol/L (-1·45 to 1·28) with blonanserin to 0·74 mmol/L (0·04 to 1·43) with quetiapine; prolactin from -2·83 ng/mL (-8·42 to 2·75) with aripiprazole to 26·40 ng/mL (21·13 to 31·67) with risperidone or paliperidone; heart rate from -0·20 bpm (-8·11 to 7·71) with ziprasidone to 12·42 bpm (3·83 to 21·01) with quetiapine; SBP from -3·40 mm Hg (-6·25 to -0·55) with ziprasidone to 10·04 mm Hg (5·56 to 14·51) with quetiapine; QTc from -0·61 ms (-1·47 to 0·26) with pimozide to 0·30 ms (-0·05 to 0·65) with ziprasidone.

Interpretation: Children and adolescents show varied but clinically significant physiological responses to individual antipsychotic drugs. Treatment guidelines for children and adolescents with a range of neuropsychiatric and neurodevelopmental conditions should be updated to reflect each antipsychotic drug's distinct profile for associated metabolic changes, alterations in prolactin, and haemodynamic alterations.

Funding: UK Academy of Medical Sciences, Brain and Behaviour Research Foundation, UK National Institute of Health Research, Maudsley Charity, the Wellcome Trust, Medical Research Council, National Institute of Health and Care Research Biomedical Centre at King's College London and South London and Maudsley NHS Foundation Trust, the Italian Ministry of University and Research, the Italian National Recovery and Resilience Plan, and Swiss National Science Foundation.

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Conflict of interest statement

Declaration of interests RAM has participated in speaker meetings for Otsuka, Karuna, and Janssen and in advisory boards for Viatris, Boehringer Ingelheim, and Karuna. ED’A has received lecture fees from Lundbeck. GS-d-P has participated in advisory and speaker meetings for Jansen and Menarini. OE has received honoraria and consulting fees from Biogen, paid to his institution. AC has received research, educational, and consultancy fees from the Italian Network for Paediatric Trials, the Cariplo Foundation, Lundbeck, and Angelini Pharma and is the chief investigator of a randomised controlled trial of seltorexant for adolescents with depression that is sponsored by Janssen. CUC has received consultancy fees as an advisor from Alkermes, Angelini, Boehringer Ingelheim, Cardio Diagnostics, Cerevel, CNX Therapeutics, Compass Pathways, Gedeon Richter, Holmusk, IntraCellular Therapies, Janssen, Johnson & Johnson, Karuna, LB Pharma, Lundbeck, MedAvante–ProPhase, Merck, Mindpax, Mitsubishi Tanabe Pharma, Neurelis, Newron, Noven, Novo Nordisk, Otsuka, Pharmabrain, PPD Biotech, Recordati, Rovi, Seqirus, SK Life Science, Sunovion, Supernus, Takeda, Teva, and Viatris; has received speaker fees from AbbVie, Alkermes, Angelini, Aristo, Boehringer Ingelheim, Cerevel, Darnitsa, Denovo, Gedeon Richter, Hikma, Janssen, Johnson & Johnson, Karuna, Lundbeck, Mylan, Otsuka, Recordati, Rovi, Seqirus, Sunovion, Sun Pharma, Takeda, Teva, and Viatris; has received honoraria from Allergan, Biogen, Relmada, Reviva, and Supernus; has provided expert testimony for Janssen and Otsuka; was on a data safety monitoring board for Compass Pathways, Denovo, Lundbeck, Relmada, Reviva, Rovi, Sage, Supernus, Tolmar, and Teva; has received grant support from Janssen and Takeda; has received royalties from UpToDate; and is a stock option holder of Cardio Diagnostics, Mindpax, LB Pharma, PsiloSterics, and Quantic. ODH has received investigator-initiated research funding from and participated in advisory and speaker meetings for Angellini, Autifony, Biogen, Boehringer Ingelheim, Eli Lilly, Heptares, Global Medical Education, Invicro, Janssen, Lundbeck, Neurocrine, Otsuka, Sunovion, Rand, Recordati, Roche, ROVI Biotech, Viatris, and Mylan. TP has participated in educational speaker meetings for Lundbeck, Otsuka, Sunovion, Janssen, Schwabe Pharma, ROVI Biotech, and Recordati and receives book royalties from Wiley Blackwell. TP and RAM co-direct Pharmatik, which designs digital resources to support treatment of mental illness. All other authors declare no competing interests.

Figures

Figure 1
Figure 1
Study selection
Figure 2
Figure 2
Network graphs of effects of antipsychotic drugs on physiological parameters in children and adolescents Treatments with direct comparisons are linked with a line; the thickness of the line corresponds to the weight of the random effects model comparing the two treatments. Numbers on connecting lines correspond to the number of trials comparing the two treatments. QTc=heart rate-corrected QT interval.
Figure 3
Figure 3
Effect of antipsychotic drugs on bodyweight (A), BMI (B), triglycerides (C), and prolactin (D) relative to placebo Colours indicate CINEMA confidence ratings in the evidence (ie, green is high, blue is moderate, purple is low, and red is very low; appendix pp 33–36). Note that scales differ between panels.
Figure 4
Figure 4
Antipsychotic physiological effects relative to placebo Antipsychotic drugs in this Kilim plot are ranked by mean difference (95% CI) for each variable except QTc, for which data are standardised mean difference (95% CI). Colours correspond to the strength of the statistical evidence supporting the relative effects of a drug versus placebo. For example, deep green indicates strong evidence that a drug is associated with an improvement in that variable compared with placebo (which, for all variables except HDL cholesterol, means a reduction in that variable). Conversely, deep red indicates strong evidence that the drug is associated with a worsening in that variable compared with placebo (which, for all variables except for HDL cholesterol, means an increase in that variable). Colours close to white indicate little evidence on whether the drug performs better or worse than placebo. QTc=heart rate-corrected QT interval.
Figure 5
Figure 5
Effect of antipsychotic drugs on fasting glucose (A), total cholesterol (B), HDL cholesterol (C), and LDL cholesterol (D) relative to placebo Colours indicate CINEMA confidence ratings in the evidence (ie, green is high, blue is moderate, purple is low, and red is very low; appendix pp 36–40). Note that scales differ between panels.
Figure 6
Figure 6
Effect of antipsychotic drugs on heart rate (A), QTc interval (B), and systolic blood pressure (C)relative to placebo Colours indicate CINEMA confidence ratings in the evidence (ie, green is high, blue is moderate, purple is low, and red is very low; appendix pp 40–42). Note that scales differ between panels. QTc=heart rate-corrected QT interval.

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