Atypical antipsychotics for autism spectrum disorder: a network meta-analysis
Notice bibliographique
Résumé
RATIONALE: Individuals with autism spectrum disorder (ASD) exhibit a wide variety of symptoms related to social interaction and behaviour. Atypical antipsychotics have been widely evaluated and prescribed to treat distressing symptoms (e.g. irritability, aggression, obsessions, repetitive behaviours, etc.) in children and adults with ASD. Still, their effects and relative efficacy remain unclear. OBJECTIVES: Primary: to assess the comparative benefits of atypical antipsychotics for irritability through network meta-analyses in children and adults with ASD at short-term follow-up. Secondary: to assess the benefits and harms of atypical antipsychotics, compared to placebo or any other atypical antipsychotic, for different symptoms (e.g. aggression, obsessive-compulsive behaviours, inappropriate speech) and side effects (e.g. extrapyramidal symptoms, weight gain, metabolic side effects) in children and adults with ASD at short-, medium- and long-term follow-up. SEARCH METHODS: We searched CENTRAL, MEDLINE, 10 other databases, and two trial registers, together with reference checking, citation searching and contact with study authors to identify studies for inclusion. The latest search was 3 January 2024. ELIGIBILITY CRITERIA: Randomised controlled trials (RCTs) comparing any atypical antipsychotic drug with placebo or another atypical antipsychotic drug for adults and children with a clinical diagnosis of ASD. OUTCOMES: Critical outcomes included irritability, aggression, weight gain, extrapyramidal side effects, obsessive-compulsive behaviours and inappropriate speech. RISK OF BIAS: We used the Cochrane RoB 2 tool to assess risk of bias in the included studies. SYNTHESIS METHODS: We performed statistical analyses using a frequentist network meta-analysis for combined estimates for the outcome irritability and a random-effects model for pairwise comparisons for other outcomes. We rated the certainty of the evidence using GRADE. INCLUDED STUDIES: We included 17 studies with 1027 randomised participants. One study evaluated adults (31 participants); the remaining 16 studies evaluated children (996 participants). The interventions were risperidone, aripiprazole, lurasidone and olanzapine. SYNTHESIS OF RESULTS: Comparative efficacy on irritability Based on the network meta-analysis, risperidone and aripiprazole may reduce symptoms of irritability compared to placebo in the short term in children with ASD (risperidone: mean difference (MD) -7.89, 95% confidence interval (CI) -9.37 to -6.42; 13 studies, 906 participants; low-certainty evidence; aripiprazole: MD -6.26, 95% CI -7.62 to -4.91; 13 studies, 906 participants; low-certainty evidence). Lurasidone probably results in little to no difference in irritability compared to placebo in the short term (MD -1.30, 95% CI -5.46 to 2.86; 13 studies, 906 participants; moderate-certainty evidence). Efficacy and safety on other outcomes We are very uncertain about the effects of atypical antipsychotics on aggression compared to placebo at short-term follow-up in children with ASD (risk ratio (RR) 1.06, 95% CI 0.96 to 1.17; 1 study, 66 participants; very low-certainty evidence). The certainty of the evidence was very low due to concerns about risk of bias and serious imprecision. We are very uncertain about the effects of atypical antipsychotics on the occurrence of weight gain (above predefined levels) compared to placebo in the short term in children with ASD (RR 2.40, 95% CI 1.25 to 4.60; 7 studies, 434 participants; very low-certainty evidence). We are also very uncertain about the effects of atypical antipsychotics on weight gain (in kilograms) compared to placebo in the short term in children with ASD (MD 1.22 kg, 95% CI 0.55 to 1.88; 3 studies, 297 participants; very low-certainty evidence). In both, the certainty of the evidence was very low due to concerns about risk of bias and serious imprecision. We are very uncertain about the effects of atypical antipsychotics on the occurrence of extrapyramidal side effects compared to placebo in the short term in children with ASD (RR 2.36, 95% CI 1.22 to 4.59; 6 studies, 511 participants; very low-certainty evidence). The certainty of the evidence was very low due to concerns about risk of bias and serious imprecision. Atypical antipsychotics may improve obsessive-compulsive behaviours compared to placebo in the short term in children with ASD (MD -1.36, 95% CI -2.45 to -0.27; 5 studies, 467 participants; low-certainty evidence). The certainty of the evidence was low due to concerns about risk of bias and heterogeneity. Atypical antipsychotics may reduce inappropriate speech compared to placebo in the short term in children with ASD (MD -1.44, 95% CI -2.11 to -0.77; 8 studies, 676 participants; low-certainty evidence). The certainty of the evidence was low due to concerns about risk of bias and heterogeneity. We were unable to evaluate the effects of other atypical antipsychotics. Furthermore, our findings on adults with autism were scarce due to the lack of available studies. AUTHORS' CONCLUSIONS: Risperidone and aripiprazole may reduce symptoms of irritability compared to placebo in children with ASD in the short term, but lurasidone probably has little to no effect on irritability compared to placebo. Other benefits and potential harms observed ranged from moderate- to very low-certainty evidence. The available data did not allow comprehensive subgroup analyses. New randomised controlled trials with larger sample sizes are needed to balance the efficacy and safety of interventions with enough certainty, which are currently scarce (or even absent in the case of the adult population). Authors should report population and intervention characteristics transparently, providing disaggregated or individual patient data when possible. Furthermore, consistent measurement methods for each outcome should be reported to avoid problems during the data synthesis process. FUNDING: This Cochrane review had no dedicated funding. REGISTRATION: Protocol available via 10.1002/14651858.CD014965.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,015 | 0,034 |
| Bibliométrie | 0,010 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».