Effects of clozapine treatment on the improvement of substance use disorders other than nicotine in individuals with schizophrenia spectrum disorders: A systematic review and meta-analysis
Bibliographic record
Abstract
Background:Antipsychotic medications are the mainstay of treatment for schizophrenia and are associated with a reduction in psychiatric hospitalization and overall mortality. Some evidence suggest that antipsychotic medications might have a varying effect on the improvement of comorbid substance use disorders (SUDs), with clozapine showing more favorable outcomes.Aim:We systematically reviewed all available evidence on effects of clozapine on the improvement of SUDs other than nicotine.Methods:Electronic searches of MEDLINE, Embase, PsycINFO, and CINHAL were conducted up to March 1, 2022. Studies of any methodological design involving two concepts: (1) clozapine and (2) SUD terms (excluding nicotine) were included. For SUD outcomes with three or more comparative studies with available raw data meta-analysis was performed. SUD outcomes not meeting criteria for meta-analysis were described qualitatively. Risk of bias was examined using “Downs and Black,” and “Q-Coh” instruments.Results:The majority of individuals in the included 31 studies were male and of European ancestry. Abstinence was the most common outcome. Most of the studies were of low-to-moderate quality, and none of the studies met all the quality criteria. Pooled findings from four observational studies in samples of patients with predominantly comorbid alcohol use disorder showed that clozapine treatment is associated with significantly higher odds of remaining abstinent. In addition clozapine was associated with decreased odds of psychiatric hospitalization in all but one observational study.Conclusions:Our systematic review and meta-analysis builds upon previous reviews, and it suggests the association of clozapine treatment with significantly higher odds of remaining abstinent from substance use and decreased likelihood of psychiatric hospitalization, compared with continuing treatment with other antipsychotic medications. Still, the validity of this association needs greater exploration and providing recommendations for the utility of clozapine in individuals without treatment-resistant psychosis and comorbid SUDs would be premature.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.041 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".