Second International Consensus Study of Antipsychotic Dosing (ICSAD-2)
Bibliographic record
Abstract
BACKGROUND: Expert consensus-based clinically equivalent dose estimates and dosing recommendations can provide valuable support for the use of drugs for psychosis in clinical practice and research. AIMS: This second International Consensus Study of Antipsychotic Dosing provides dosing equivalencies and recommendations for newer drugs for psychosis and previously reported drugs with low consensus. METHODS: We used a two-step Delphi survey process to establish and update consensus with a broad, international sample of clinical and research experts regarding 26 drug formulations to obtain dosing recommendations (start, target range, and maximum) and estimates of clinically equivalent doses for the treatment of schizophrenia. Reference agents for equivalent dose estimates were oral olanzapine 20 mg/day for 15 oral and 7 long-acting injectable (LAI) agents and intramuscular haloperidol 5 mg for 4 short-acting injectable (SAI) agents. We also provide a contemporary list of equivalency estimates and dosing recommendations for a total of 44 oral, 16 LAI, and 14 SAI drugs for psychosis. RESULTS: = 72) from 24 countries provided equivalency estimates and dosing recommendations for oral, LAI, and SAI formulations. Consensus improved from survey stages I to II. The final consensus was highest for LAI formulations, intermediate for oral agents, and lowest for SAI formulations of drugs for psychosis. CONCLUSIONS: As randomized, controlled, fixed, multiple-dose trials to optimize the dosing of drugs for psychosis remain rare, expert consensus remains a useful alternative for estimating clinical dosing equivalents. The present findings can support clinical practice, guideline development, and research design and interpretation involving drugs for psychosis.
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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 | 0.347 | 0.362 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".