T233. DEFINING TREATMENT RESPONSE AND RESISTANCE IN FIRST EPISODE SCHIZOPHRENIA
Bibliographic record
Abstract
Although a substantial proportion of individuals with schizophrenia fail to respond to first-line dopaminergic blocking medications and are Treatment Resistant (TR), identifying these subjects prospectively remains challenging. Though clinically defined only after multiple treatment trials, TR is suspected to reflect a stable neurobiological phenomenon that can be identified even at the first episode of schizophrenia (FES). Establishing clear expectations for symptom improvement following antipsychotic initiation would facilitate development of objective thresholds for determining lack of efficacy. The Treatment Response and Resistance in Psychosis (TRIPP; Howes et al, 2017) working group has recently published consensus guidelines which define lack of response as a <20% improvement in psychotic symptoms. However, given that most patients with FES respond robustly to antipsychotics (Robinson et al, 1999), FES specific criteria for prospective identification of TR are warranted. We examined two symptom improvement thresholds across positive and negative symptom domains at 6 months in FES to investigate poor response (PR) as a proxy measure of early TR. We then examined the baseline/early clinical features that best prospectively predicted PR+ status. Given the estimated prevalence of TR is approximately 33%, we hypothesized that a comparable number (ie, 1/3rd) of individuals with FES would meet PR criteria using less a 50% response threshold, rather than a more stringent 20% threshold for determining symptomatic response. Furthermore, we hypothesized that very early lack of response would be associated with PR at 6 months. Data from a longitudinal naturalistic cohort study of patients treated at the Prevention and Early Intervention Program for Psychosis (PEPP) in London, Ontario, Canada collected between 2002 and 2007 were used for this analysis. Only individuals meeting criteria for a primary psychotic disorder that were medication compliant were included. Positive and negative symptoms of psychosis were assessed using the SAPS (Andreasen, 1983) and SANS (Andreasen, 1984) at baseline, and at months 1, 2, 3, and 6. Treatment was administered in a naturalistic setting and followed clinical guidelines for the treatment of FES. Applying a 20% and 50% symptom improvement threshold for defining PR resulted in 2.2% and 14% rates for positive symptom PR, 33% and 60.9% rates of negative symptom PR, and 12% and 37.0% rates of total symptom PR at 6 months. Logistic regression analyses demonstrated that poor premorbid functioning, having a longer duration of untreated illness, and limited overall treatment response at months one and two were significantly associated with being PR+ (<50% improvement in total symptoms) at 6 months. This is the first study to our knowledge to investigate the symptom response thresholds suggested by TRIPP in FES. Our results suggest that including negative symptoms (either alone, with a 20% criteria for improvement, or in addition to positive symptoms, with a 50% improvement threshold) is necessary to identify the expected proportion of TR subjects prospectively in a FES sample. We propose that failing to achieve at least a 50% improvement in total symptoms, or at least 20% change in negative symptom severity by 6 months may be an early clinical indicator of eventual TR. On an optimistic note, we speculate that it may be possible to determine clozapine-eligibility as early as 6 months by using this approach. However, further studies are warranted to investigate the utility of this symptom threshold criteria in larger samples of patients with FES.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".