Efficacy and safety of clozapine in psychotic disorders—a systematic quantitative meta-review
Bibliographic record
Abstract
A recent increase in the literature regarding the evidence base for clozapine has made it increasingly difficult for clinicians to judge "best evidence" for clozapine use. As such, we aimed at elucidating the state-of-the-art for clozapine with regard to efficacy, effectiveness, tolerability, and management of clozapine and clozapine-related adverse events in neuropsychiatric disorders. We conducted a systematic PRISMA-conforming quantitative meta-review of available meta-analytic evidence regarding clozapine use. Primary outcome effect sizes were extracted and transformed into relative risk ratios (RR) and standardized mean differences (SMD). The methodological quality of meta-analyses was assessed using the AMSTAR-2 checklist. Of the 112 meta-analyses included in our review, 61 (54.5%) had an overall high methodological quality according to AMSTAR-2. Clozapine appears to have superior effects on positive, negative, and overall symptoms and relapse rates in schizophrenia (treatment-resistant and non-treatment-resistant subpopulations) compared to first-generation antipsychotics (FGAs) and to pooled FGAs/second-generation antipsychotics (SGAs) in treatment-resistant schizophrenia (TRS). Despite an unfavorable metabolic and hematological adverse-event profile compared to other antipsychotics, hospitalization, mortality and all-cause discontinuation (ACD) rates of clozapine surprisingly show a pattern of superiority. Our meta-review outlines the superior overall efficacy of clozapine compared to FGAs and most other SGAs in schizophrenia and suggests beneficial efficacy outcomes in bipolar disorder and Parkinson's disease psychosis (PDP). More clinical studies and subsequent meta-analyses are needed beyond the application of clozapine in schizophrenia-spectrum disorders and future studies should be directed into multidimensional clozapine side-effect management to foster evidence and to inform future guidelines.
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.033 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".