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Enregistrement W2885976838 · doi:10.18553/jmcp.2018.24.8.759

Projecting the Potential Effect of Using Paliperidone Palmitate Once-Monthly and Once-Every-3-Months Long-Acting Injections Among Medicaid Beneficiaries with Schizophrenia

2018· article· en· W2885976838 sur OpenAlexaff
Anirban Basu, Carmela Benson, Larry Alphs

Notice bibliographique

RevueJournal of Managed Care & Specialty Pharmacy · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueSchizophrenia research and treatment
Établissements canadiensInstitute of Health Economics
Organismes subventionnairesJanssen Scientific Affairs
Mots-clésPaliperidone PalmitateMedicineMedicaidSchizophrenia (object-oriented programming)AntipsychoticDiscontinuationPaliperidonePopulationRandomized controlled trialInclusion and exclusion criteriaInternal medicinePsychiatryEnvironmental healthAlternative medicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Once-monthly and once-every-3-months long-acting injectable (LAI) formulations of paliperidone palmitate (PP1M and PP3M, respectively) are available for the treatment of patients with schizophrenia. However, information on the comparative effectiveness and costs of using these LAIs versus oral antipsychotics (OAs) is not available. The population effectiveness of using these treatments is also not known. OBJECTIVE: To project the effect of using PP1M and PP3M LAIs on psychiatric (Psych) and all-cause (AC) hospitalization rates over 18 months in patients with schizophrenia receiving Medicaid and treated with OAs. METHODS: A decision model, informed by data from 3 randomized controlled trials (PRIDE [NCT01157351], 3001 [NCT00111189], and 3012 [NCT01529515]), was developed to compare 3 strategies: (a) initiating OA and switching only to OA; (b) initiating with PP1M and continuing PP1M if the patient was stable at 6 months (or switching to OA if unstable; PP1M→PP1M); and (c) initiating with PP1M and switching to PP3M if the patient was stable at 6 months (or switching to OA if unstable; PP1M→PP3M). PRIDE data were used to inform the first 6-month outcomes; 3001 and 3012 data were used to inform outcomes in stable patients over the following 12 months. The primary outcome for this decision model study was Psych hospitalizations. AC hospitalizations and time to discontinuation were also assessed. Outcomes from each arm and time portions within an arm were reweighted to reflect the distribution of patient characteristics found in the real-world Medicaid sample with PRIDE trial inclusion/exclusion criteria applied. Several validation exercises were carried out to ensure that the reweighted results could reproduce observed outcomes in the Medicaid sample. RESULTS: Our final target real-world sample size was N=4,609. We found that in the Medicaid sample, compared with initiating treatments with OA, the PP1M→PP1M strategy was projected to produce a per patient decrease of 0.27 (95% CI = -0.43-0.97) and 0.28 (95% CI = -0.28-0.84) in Psych- and AC-related hospitalizations, respectively. Similarly, the PP1M→PP3M strategy was projected to produce a per patient decrease of 0.31 (95% CI = -0.27-0.87) in both Psych- and AC-related hospitalizations over OA. Validation exercises ensured that the reweighting methodology used could replicate observed outcomes in the Medicaid sample. These incremental reductions in hospitalization rates are worth about $3.4-$3.8 billion over an 18-month period in patients with schizophrenia receiving Medicaid. CONCLUSIONS: Our results suggest that using PP1M and PP3M treatment strategies for patients with schizophrenia receiving Medicaid could result in reduced hospitalizations. This finding, along with improvement to patients' health, should be considered when assessing the value of these LAIs. DISCLOSURES: This study was supported by Janssen Scientific Affairs and by unrestricted funds from a consortium of 12 biomedical life sciences companies to the University of Washington. Janssen Scientific Affairs was responsible for the design and conduct of the study; the collection, management, analysis, and interpretation of data; the preparation, review, and approval of the manuscript; and the decision to submit the manuscript for publication. Basu received financial support from Janssen Pharmaceuticals, and his time on this project was also partly covered through unrestricted gift funds from the consortium of biomedical life sciences companies. Benson and Alphs are employees of Janssen Scientific Affairs and are stockholders of Johnson & Johnson. Opinions expressed here do not necessarily reflect those of the University of Washington. This study was presented as a poster at the AMCP Managed Care & Specialty Pharmacy 2017 Annual Meeting; March 27-30, 2017; Denver, CO.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,424
Score d'incertitude au seuil0,826

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,018
Tête enseignante GPT0,318
Écart entre enseignants0,300 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations11
Publié2018
Routes d'admission1
Résumé présentoui

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