Medication Exposure and Mortality in Patients With Schizophrenia
Bibliographic record
Abstract
Importance: The use of antipsychotics, antidepressants, and benzodiazepines may influence the risk of mortality in people with schizophrenia. However, many observational studies have not accounted for immortal time bias (ITB), which occurs when there is a period during which patients in the exposed group are necessarily alive and misclassified as exposed (the period between start of follow-up and initiation of drug). Ignoring ITB may lead to misinterpretation of the association between these drugs and mortality. Objectives: To examine whether the cumulative dose of antipsychotics, antidepressants, and benzodiazepines is associated with mortality risk in patients with schizophrenia and discuss the potential impacts of ignoring ITB. Design, Setting, and Participants: This cohort study used administrative data from Québec, Canada, including patients aged 17 to 64 years diagnosed with schizophrenia between January 1, 2002, and December 31, 2012. Data analysis was performed from June 22, 2022, to September 30, 2024. Main Outcomes and Measures: The primary outcome was all-cause mortality, with follow-up from January 1, 2013, to December 31, 2017, or until death. Mortality risk was assessed for low, moderate, and high exposure to antipsychotics, antidepressants, and benzodiazepines. Cox proportional hazards regression models with time-fixed exposure (not controlling for ITB) and time-dependent exposure (controlling for ITB) were performed. Results: The cohort included 32 240 patients (mean [SD] age, 46.1 [11.6] years; 19 776 [61.3%] men), of whom 1941 (6.0%) died during follow-up. No dose-response association was found for antipsychotics with mortality using the time-fixed method. However, high-dose antipsychotic use was associated with increased mortality after correcting for ITB (adjusted hazard ratio [AHR], 1.28; 95% CI, 1.07-1.55; P = .008). Antidepressants showed a reduced mortality risk using the time-fixed method, but only at high doses when correcting for ITB (AHR, 0.86; 95% CI, 0.74-1.00; P = .047). Benzodiazepines were associated with increased mortality risk regardless of the method. Conclusions and Relevance: The findings of this study do not dispute the known efficacy of antipsychotics in schizophrenia, but they call into question the magnitude of long-term mortality benefits.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".