Sex Selection Bias in Schizophrenia Antipsychotic Trials
Bibliographic record
Abstract
The sex prevalence of schizophrenia is approximately equal, and yet clinical trials of new therapeutic drugs have been conducted, for the most part, with male participants. The authors reviewed the percentage of women in schizophrenia clinical trials of the new "atypical" antipsychotic medications. MEDLINE and Cochrane databases were searched for English-language randomized controlled trials involving risperidone, olanzapine, quetiapine, ziprasidone, and aripiprazole. Studies with a sample size of more than 50 and a subject diagnosis of schizophrenia, schizophrenia spectrum disorder, or broad psychosis were included for review. For each study, the following items were abstracted: source of support, pharmacotherapy, site location, treatment setting, patient phase, psychotic episode number, duration, number of men and women in the total sample, mean age of the sample, and the presence of women-specific inclusion/exclusion criteria. Sixty-seven published studies met criteria. The median percentage of women in the total sample was 33.3%, the minimum was 6.7%, and the maximum was 71.2%. A stepwise linear regression analysis showed that age (younger samples), center location (Unites States and Canada), treatment patient setting (inpatient), and ziprasidone trials were all associated with relatively lower percentages of women. Sex differences in antipsychotic pharmacokinetics and pharmacodynamics that may result in differential effectiveness and susceptibility to adverse effects cannot be ascertained when the percentage of women in clinical trials is as low as it is. The increasing shift toward outpatient rather than inpatient drug trials may help to increase the proportion of women.
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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 | 0.367 | 0.566 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".