Utilization of Old- Versus New-Generation Biologics for Plaque Psoriasis for Public and Private Payers in Canada
Notice bibliographique
Résumé

 Issue: Recent health technology reviews by CADTH, including a national Environmental Scan of biologics for PsO across public drug plans and a review of the clinical evidence on the comparative effectiveness of biologics for PsO, have suggested that the appropriate use of biologics for the treatment of plaque psoriasis (PsO) may favour new-generation biologics (i.e., anti-interleukin [IL]-17 and anti-IL-23 inhibitors) over old-generation biologics (i.e., anti–tumour necrosis factor and anti-IL-12/23 biologics). Specifically, these reviews found:
 
 New-generation biologics for PsO consistently demonstrated greater efficacy compared to old-generation biologics in recent head-to-head trials (e.g., AMAGINE-2 and AMAGINE−3, FIXTURE, IMMvent, NAVIGATE, UltIMMA-1 and UltIMMA−2, UNCOVER-2 and UNCOVER-3, and VOYAGE-1 and VOYAGE−2).
 Formulary listings of the old-generation biologics mostly predate any pan-Canadian Pharmaceutical Alliance (pCPA) agreements, which increases the likelihood of fewer product listing agreements (PLAs) with public payers for these drugs, whereas all new-generation biologics have all undergone pCPA negotiations. For private payer formulary listings, PLAs are not publicly disclosed although, according to the Canadian Life and Health Insurance Association (CLHIA), they are likely to occur.
 Old-generation biologics have reached the expiration of their exclusivity periods (i.e., time when an originator biologic is protected from biosimilar competition), whereas all new-generation biologics currently have active exclusivity status.
 
 
 
 
 Approach: A national utilization study was conducted to assess the utilization patterns of old- versus new-generation biologics in PsO for both public payers (using Canadian Institute for Health Information [CIHI] data) and private payers (using Reformulary and CLHIA data), prescribing patterns (market share and average costs) for old- versus new-generation biologics for both public and private insurance among new and existing users, and expenditures (excluding PLAs) on biologics for PsO after LoE by public and private payers.
 Findings:
 
 Although new-generation biologics in PsO are associated with greater efficacy, approximately 44% of patients newly initiating a biologic across public and private drug plans in Canada were prescribed an old-generation biologic in 2020.
 Average annual cost per new patient was typically higher for old-generation originator biologics (range = $11,645 to $16,047) versus new-generation biologics (range = $8,303 to $15,229) across public payers. Ustekinumab is associated with the highest cost estimate among new patients within public drug plans and, despite having expired exclusivity status, does not have a marketed biosimilar option available.
 Canadian taxpayers (i.e., public and private drug spending) have spent up to $9 billion (gross expenditures) on all claims for originator biologics indicated for PsO that have lost exclusivity between 2016 and 2020. To put this in perspective, analyses of data from the National Prescription Drug Utilization Information System (NPDUIS) revealed that, in Canada, spending on oncology drugs in the latest reported year (2019) was $3.9 billion and spending on the top 50 drugs in the 2019–2020 fiscal year was $4.3 billion.
 
 
 Implications for policy-makers: Given the potential for improved efficacy and lower costs of new-generation biologics, the promotion of the appropriate use of biologics in PsO should be considered by payers.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».