Treatment Response to Olanzapine and Haloperidol and its Association with Dopamine D <sub>2</sub> Receptor Occupancy in First-Episode Psychosis
Bibliographic record
Abstract
OBJECTIVE: Response to typical antipsychotic medication has been associated with achieving a level of striatal dopamine D2 receptor occupancy in the range of 65% to 70%. We undertook this study to determine whether response to the atypical antipsychotic olanzapine occurs at lower levels of D2 receptor occupancy. METHOD: Eighteen patients who presented with a first episode of psychosis were randomized to receive olanzapine 5 mg daily or haloperidol 2 mg daily in a double-blind design. We acquired positron emission tomography (PET) scans using the D2 ligand [11C]raclopride within the first 15 days of treatment to determine the percentage of D2 receptors occupied by the medication. According to response, dosage was then adjusted to a maximum dosage of 20 mg daily of either drug. PET scans were repeated after 10 to 12 weeks of treatment. RESULTS: At the first PET scan, the 8 olanzapine-treated patients had significantly lower D2 receptor occupancies (mean 63.4%, SD 7.3) than those observed in the 10 patients treated with haloperidol (mean 73.0%, SD 6.1). When patients were rescanned following dosage adjustment, mean D2 receptor occupancies were greater than 70% in both groups. D2 receptor occupancies did not differ significantly between the olanzapine-treated group (mean 72.0%, SD 5.7) and the haloperidol-treated group (mean 78.7%, SD 7.6). CONCLUSIONS: These results suggest that, in patients being treated for a first episode of psychosis, olanzapine has its antipsychotic effect at approximately the same levels of D2 receptor occupancy as are achieved with low dosages of haloperidol.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".