F112. PRESCRIBING PATHWAYS TO CLOZAPINE CO-THERAPY WITH ANTIPSYCHOTICS: A SURVEY OF TERTIARY CARE PSYCHIATRISTS TREATING SCHIZOPHRENIA WITH CLOZAPINE AND ADDITIONAL ANTIPSYCHOTICS
Bibliographic record
Abstract
Clozapine remains the medication of choice for schizophrenia not responsive to monotherapy. For the approximately 30% of clozapine refractory patients there is little evidence to guide the clinician. Ineffective clozapine trials appear to lead to combination therapy, although evidence is largely limited to aripiprazole and amisulpride, leaving clinicians with minimal options for this most challenging population. Antipsychotic polypharmacy rates are high, including with clozapine, and few studies address clinician attitudes and rationales for the practice. We used a custom-generated questionnaire with multiple-choice questions and open-ended follow-up questions to survey clinicians at The Royal Ottawa Mental Health Centre Schizophrenia Program, a tertiary treatment program following approximately 1500 patients suffering treatment refractory and otherwise difficult to treat schizophrenia. Physicians prescribing clozapine with at least one additional antipsychotic were interviewed with the aim of capturing specific rationales for antipsychotic co-prescription with clozapine. Primary outcome was the reason provided for co-prescription of additional antipsychotics with clozapine. Secondary outcomes included clinical impression of illness severity, number of cases for which clinicians intended eventual monotherapy and preferred strategies for combining antipsychotics with clozapine. Nine physicians were interviewed, and surveys were completed for 104 of 285 clients on clozapine, of whom, 136 (47.7%) were on 1–3 additional antipsychotics. The most common reason for clozapine antipsychotic polypharmacy was ‘reduction of positive symptoms,’ cited in 90 of 104 cases, with specific reason of selecting for ‘additional dopaminergic activity’ in 76 cases; followed by ‘reduction of negative symptoms;’ ‘reduction of affective symptoms;’ and ‘management of concurrent symptoms,’ each noted in 26 cases. Reasons for co-prescription were highly varied with 17 different motives provided. There were 19 cases of polypharmacy while switching medications, and 16 cases of inherited polypharmacy, all with intent to discontinue. Preferred combination strategies were highly idiosyncratic. Aripiprazole, oral or injectable, was most often cited by 6 out of 9 physicians. Physicians described their assessment of clozapine polypharmacy as ‘improved’ in 76 cases, ‘worsened,’ in 9, ‘better but with side effects’ in 6, and ‘no change’ in 7. Ratings on the CGI-I showed 17 ‘very much improved,’ 40 ‘much improved,’ 49 ‘minimally improved,’ 22 ‘no change,’ 4 ‘minimally worse,’ and 1 ‘much worse.’ In keeping with other studies, antipsychotic co-prescription was most commonly initiated by physicians in a tertiary care schizophrenia program for poorly controlled positive symptoms. Aripiprazole was a frequent choice however, strategies were highly individual, and no clear guidance on a second antipsychotic is possible from this data. Interestingly, physicians rated the patient as ‘improved’ in 76 of 98 answers however, CGI-I scores were more modest with ratings of ‘minimally improved,’ or ‘no change’ for 71 out of 133 answers. This makes a strong case for objective, prospective measuring of clinical response as a safety and quality improvement measure, especially as polypharmacy is associated with increased morbidity. Our results emphasize that even in the hands of skilled practitioners, treatment refractory schizophrenia is a highly morbid illness in dire need of innovative and evidence-based guidance to reduce suffering and improve outcomes. When using combination treatment, reliable measurements of response would help maximize outcomes and safety of patients resistant to treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".