S40. COMBINING PHARMACOTHERAPY OF BI 425809 WITH COMPUTERISED COGNITIVE TRAINING IN PATIENTS WITH SCHIZOPHRENIA: INITIAL EXPERIENCE OF A LARGE-SCALE MULTICENTRE RANDOMISED CLINICAL TRIAL
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».