S30. COMBINING PHARMACOTHERAPY OF BI 425809 WITH COMPUTERIZED COGNITIVE TRAINING IN PATIENTS WITH SCHIZOPHRENIA: A RANDOMIZED TRIAL METHODOLOGY
Notice bibliographique
Résumé
Trials of pharmacotherapies targeting cognition in schizophrenia have produced mainly negative results, and there are no approved cognition-enhancing pharmacological treatments available for patients with schizophrenia. This may be due in part to varying levels of concurrent cognitive stimulation, particularly for pharmacotherapies targeting neuroplasticity, which is activity-dependent (i.e. responds to cognitive demand). Often, the surroundings and environment of patients with schizophrenia provide only a low level of cognitive demand. At-home computerized cognitive training (CCT) can be one way to increase the level of environmental cognitive stimulation for these patients. BI 425809, a glycine transporter 1 inhibitor, increases glycine in the synaptic cleft and thus should lead to improved glutamatergic neurotransmission, synaptic neuroplasticity, and cognition. We describe a large randomized multicenter trial conducted across several countries that aims to explore whether enhanced cognitive stimulation through at-home CCT combined with BI 425809 pharmacotherapy could significantly improve cognition in patients with schizophrenia. This double-blind, parallel group trial plans to recruit patients with schizophrenia on stable antipsychotic therapy, across approximately 40 centers in 7 countries. We plan to randomize 200 patients who are compliant with CCT during a 2-week run-in period in a 1:1 ratio to either BI 425809 or placebo once daily for 12 weeks. The at home CCT should be optimally performed across 3–5 sessions (approximately 2.5 hours in total) per week. The primary endpoint will be change from baseline in neurocognitive function, measured by the neurocognitive composite score of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) after 12 weeks of treatment. The neurocognitive composite score was selected specifically because it excludes the social cognition domain, which is typically targeted by separate training procedures. Novel exploratory endpoints include the Virtual Reality Functional Capacity Assessment Tool (VRFCAT) to assess skills for daily functioning and the Balloon Effort task to assess the role of motivation in cognitive performance and also in patients’ willingness to comply with at-home CCT. Scores from the Patient Reported Experience of Cognitive Impairment in Schizophrenia (PRECIS), which is being developed to assess patients’ subjective experiences of cognitive impairment in schizophrenia, will also be assessed in a subset of patients. Initiation of the trial is planned for February 2019 and the last patient out is planned for December 2020. Results are expected in early 2021. This trial is critical to the field for several reasons. Firstly, the results will show if there is an enhanced benefit to combining pharmacotherapy with increased cognitive stimulation through at-home CCT in patients with schizophrenia. Second, the trial will evaluate the impact of BI 425809 with adjunctive CCT on outcomes relating to patients’ daily functioning, including the novel virtual reality test, VRFCAT. Third, the role of motivation in cognition, CCT compliance, and CCT performance will be explored. Finally, this trial will demonstrate if at-home CCT can be effectively implemented in a large trial across many centers and several countries. One key strength of this trial is the relatively large sample size which should result in robust data. Funding: Boehringer Ingelheim International GmbH (1346.38)
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 | 0,013 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,022 | 0,004 |
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 ».