Clozapine for Treatment-Resistant Disruptive Behaviors in Youths With Autism Spectrum Disorder Aged 10-17 Years: Protocol for an Open-Label Trial
Bibliographic record
Abstract
BACKGROUND: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition emerging in early childhood, characterized by core features such as sociocommunicative deficits and repetitive, rigid behaviors, interests, and activities. In addition to these, disruptive behaviors (DB), including aggression, self-injury, and severe tantrums, are frequently observed in pediatric patients with ASD. The atypical antipsychotics risperidone and aripiprazole, currently the only Food and Drug Administration-approved treatments for severe DB in patients with ASD, often encounter therapeutic failure or intolerance. Given this, exploring pharmacological alternatives for more effective management of DB associated with ASD is essential. Clozapine, noted for its unique antiaggressive effects in schizophrenia and in various treatment-resistant neuropsychiatric disorders, independent from its antipsychotic efficacy, remains underexplored in youths with ASD facing severe and persistent DB. OBJECTIVE: This study aimed to evaluate the efficacy, tolerability, and safety of clozapine for treatment-resistant DB in youths with ASD. METHODS: This is a prospective, single-center, noncontrolled, open-label trial. After a cross-titration phase, 31 patients with ASD aged 10-17 years and with treatment-resistant DB received a flexible dosage regimen of clozapine (up to 600 mg/day) for 12 weeks. Standardized instruments were applied before, during, and after the treatment, and rigorous clinical monitoring was performed weekly. The primary outcome was assessed using the Irritability Subscale of the Aberrant Behavior Checklist. Other efficacy measures include the Clinical Global Impression Severity and Improvement, the Swanson, Nolan, and Pelham questionnaire-IV, the Childhood Autism Rating Scale, and the Vineland Adaptive Behavior Scale. Safety and tolerability measures comprised adverse events, vital signs, electrocardiography, laboratory tests, physical measurements, and extrapyramidal symptoms with the Simpsons-Angus Scale. Statistical analysis will include chi-square tests with Monte Carlo simulation for categorical variables, paired t tests or Wilcoxon tests for continuous variables, and multivariate linear mixed models to evaluate the primary outcome, adjusting for confounders. RESULTS: Recruitment commenced in February 2023. Data collection was concluded by April 2024, with analysis ongoing. This article presents the protocol of the initially planned study to provide a detailed methodological description. The results of this trial will be published in a future paper. CONCLUSIONS: The urgent need for effective pharmacological therapies in mitigating treatment-resistant DB in pediatric patients with ASD underscores the importance of this research. Our study represents the first open-label trial to explore the anti-aggressive effects of clozapine in this specific demographic, marking a pioneering step in clinical investigation. Adopting a pragmatic approach, this trial protocol aims to mirror real-world clinical settings, thereby enhancing the applicability and relevance of our findings. The preliminary nature of future results from this research has the potential to pave the way for more robust studies and emphasize the need for continued innovation in ASD treatment. TRIAL REGISTRATION: Brazilian Clinical Trials Registry RBR-54j3726; https://ensaiosclinicos.gov.br/rg/RBR-54j3726. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58031.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".