A meta-analysis of controlled studies comparing the association between clozapine and other antipsychotic medications and the development of neutropenia
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Bibliographic record
Abstract
BACKGROUND: In most countries, clozapine can only be prescribed with regular monitoring of white blood cell counts because of concerns that clozapine has a stronger association with neutropenia than other antipsychotics. However, this has not been previously demonstrated conclusively with meta-analysis of controlled studies. METHODS: The aim of this study was to assess the strength of the association between clozapine and neutropenia when compared to other antipsychotic medications by a meta-analysis of controlled studies. An electronic search of Medline (1948-2018), PsycINFO (1967-2018) and Embase (1947-2018) using search terms (clozapine OR clopine OR clozaril OR zaponex) AND (neutropenia OR agranulocytosis) was undertaken. Random-effects meta-analysis using Mantel-Haenszel risk ratio was used to assess the strength of the effect size. RESULTS: We located 20 studies that reported rates of neutropenia associated with clozapine and other antipsychotic medications. The risk ratio was not significantly increased in clozapine-exposed groups compared to exposure to other antipsychotic medications (Mantel-Haenszel risk ratio = 1.45, 95% confidence interval = [0.87, 2.42]). This also applied to severe neutropenia (absolute neutrophil count < 500 per µL) when compared to other antipsychotics (Mantel-Haenszel risk ratio = 1.65, 95% confidence interval = [0.58, 4.71]). The relative risk of neutropenia associated with clozapine exposure was not significantly associated with any individual antipsychotic medication. CONCLUSION: Data from controlled trials do not support the belief that clozapine has a stronger association with neutropenia than other antipsychotic medications. This implies that either all antipsychotic drugs should be subjected to haematological monitoring or monitoring isolated to clozapine is not justified.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it