S40. COMBINING PHARMACOTHERAPY OF BI 425809 WITH COMPUTERISED COGNITIVE TRAINING IN PATIENTS WITH SCHIZOPHRENIA: INITIAL EXPERIENCE OF A LARGE-SCALE MULTICENTRE RANDOMISED CLINICAL TRIAL
Bibliographic record
Abstract
Abstract Background There are currently no approved medications for cognition in patients with schizophrenia. BI 425809, a glycine transporter 1 inhibitor, increases glycine in the synaptic cleft and may improve glutamatergic neurotransmission, synaptic neuroplasticity, and cognition. Pharmacotherapies targeting neuroplasticity may require concurrent cognitive stimulation, and often the surroundings of patients with schizophrenia provide only a low level of cognitive demand. At-home computerised cognitive training (CCT) should increase the level of cognitive stimulation for these patients. Combining CCT with pharmacotherapy could therefore improve cognition in patients with schizophrenia. CCT studies are currently limited in scale and are associated with challenges, such as patient compliance. This ongoing study explores whether at-home CCT combined with BI 425809 could improve cognition, as compared with patients on at-home CCT and placebo, in patients with schizophrenia. Here, we provide an initial reflection on the experiences and challenges associated with setting up this large-scale clinical trial, in addition to an update on recruitment trajectories. Methods This is a Phase II, double-blind, placebo-controlled, parallel group trial in patients with schizophrenia on stable antipsychotic therapy, across ~50 centres in 6 countries. Recruitment commenced in June 2019. Patients (aged 18–50 years) must demonstrate compliance with CCT during a 2-week run-in period; this means completing at least 2 hours/week (i.e. 4 hours total during screening). Only CCT-compliant patients are randomised (1:1) to BI 425809 or placebo once daily on top of CCT for 12 weeks. The target duration for at-home CCT is ~30 hours, across 3–5 sessions (2.5 hours total) per week. The primary endpoint is change from baseline in neurocognitive composite score of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery after 12 weeks of treatment. Novel exploratory endpoints include the Virtual Reality Functional Capacity Assessment Tool to assess daily functioning and the Balloon Effort Task to assess motivation in cognitive performance and, its association with patients’ willingness to comply with at-home CCT. Results To date, 32 patients have been screened and 11 randomised (21 patients failed screening, primarily due to non-compliance with CCT run-in). The last patient out is planned for December 2020 and results are expected in Q1 2021. Patients randomised so far (n=11; 82% male) have a mean age of 33 years; those who failed screening (n=21; 67% male) have a mean age of 36 years. Mean MCCB total scores for the two groups are 30.9 and 22.3; Positive and Negative Syndrome Scale (PANNS) total scores: 71.3 vs 77.9; and PANNS negative symptom scores: 20.5 vs 20.3, for the randomised and screen failure patients, respectively. Discussion It is expected that the results of this trial will help to: indicate if there is an enhanced benefit of combining pharmacotherapy with cognitive stimulation through at-home CCT; and determine the role of motivation in CCT compliance and performance in patients with schizophrenia. The main reason for screen failures was non-compliance with CCT run-in, underscoring the relevance of coaching and motivational accompaniment to promote adherence to CCT. The results will indicate if large-scale implementation of at-home CCT across multiple centres and several countries is feasible.
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".