Population Pharmacokinetics of Perphenazine in Schizophrenia Patients From CATIE: Impact of Race and Smoking
Bibliographic record
Abstract
The goal of the study was to characterize population pharmacokinetics (PPK) for perphenazine in patients with schizophrenia from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE). Patients (n = 156) received 8 to 32 mg of perphenazine daily for 14 to 600 days for a total of 421 plasma concentrations measurements. Nonlinear mixed-effects modeling was used to determine PPK characteristics of perphenazine. One- and 2-compartment models with various random effect implementations and mixture distributions were evaluated. Objective function values and goodness-of-fit plots were used as model selection criteria. Age, weight, sex, race, smoking, and concomitant medications were evaluated as covariates. A 1-compartment linear model with proportional error best described the data. The population mean clearance and volume of distribution for perphenazine were 483 L/h and 18 200 L, respectively. Race and smoking status had significant impacts on perphenazine clearance estimates. In addition, the estimated population mean clearance was 48% higher in nonsmoking African Americans than in nonsmoking other races (512 L/h vs 346 L/h). Active smokers eliminated perphenazine 159 L/h faster than nonsmokers in each race. Clearances for smoking African Americans versus smokers in other races were 671 L/h versus 505 L/h, respectively.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".