Relationship Between Dopamine D<sub>2</sub> Occupancy, Clinical Response, and Side Effects: A Double-Blind PET Study of First-Episode Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: Since all antipsychotics block dopamine D(2) receptors, the authors investigated how well D(2) receptor occupancy in vivo predicts clinical response, extrapyramidal side effects, and hyperprolactinemia. METHOD: In a double-blind study, 22 patients with first-episode schizophrenia were randomly assigned to 1.0 or 2. 5 mg/day of haloperidol. After 2 weeks of treatment, D(2) receptor occupancy was determined with [(11)C]raclopride and positron emission tomography, and clinical response, extrapyramidal side effects, and prolactin levels were measured. Patients who showed adequate responses continued taking their initial doses, those who did not respond had their doses increased to 5.0 mg/day, and evaluations were repeated at 4 weeks for all patients. RESULTS: The patients showed a wide range of D(2) occupancy (38%-87%). The degree of receptor occupancy predicted clinical improvement, hyperprolactinemia, and extrapyramidal side effects. The likelihood of clinical response, hyperprolactinemia, and extrapyramidal side effects increased significantly as D(2) occupancy exceeded 65%, 72%, and 78%, respectively. CONCLUSIONS: The study confirms that D(2) occupancy is an important mediator of response and side effects in antipsychotic treatment. The data are consistent with a "target and trigger" hypothesis of antipsychotic action, i.e., that the D(2) receptor specificity of antipsychotics permits them to target discrete neurons and that their antagonist properties trigger within those neurons intracellular changes that ultimately beget antipsychotic response. While limited to haloperidol, the relationship between D(2) occupancy and side effects in this study helps explain many of the observed clinical differences between typical and atypical antipsychotics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".