Meta‐analysis examining the epidemiology of clozapine‐associated neutropenia
Bibliographic record
Abstract
BACKGROUND: Clozapine is associated with life-threatening neutropenia. There are no previous meta-analyses of the epidemiology of clozapine-associated neutropenia. OBJECTIVES: To determine the cumulative incidence of mild, moderate and severe neutropenia, incidence of death related to severe neutropenia, case fatality rate of neutropenia and the longitudinal incidence of neutropenia following exposure to clozapine. DATA SOURCES: A systematic search of Medline, EMBASE and PsycINFO using search terms [clozapine OR clopine OR zaponex OR clozaril] AND [neutropenia OR agranulocytosis]. METHODS: Random effects meta-analysis to determine event rates and longitudinal incidence of events per 100 person-years of exposure. RESULTS: A total of 108 studies were included. The incidence of clozapine-associated neutropenia was 3.8% (95% CI: 2.7-5.2%) and severe neutropenia 0.9% (95% CI: 0.7-1.1%). The incidence of death related to neutropenia following prescription of clozapine was 0.013% (95% CI: 0.01-0.017%). The case fatality rate of severe neutropenia was 2.1% (95% CI: 1.6-2.8%). The peak incidence of severe neutropenia occurred at one month of exposure and declined to negligible levels after one year of treatment. CONCLUSION: Severe neutropenia associated with clozapine is a rare event and occurs early with a substantial decline in risk after one year of exposure. Death from clozapine-associated neutropenia is extremely rare. Implications for haematological monitoring are discussed.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.046 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".