Real-world cost effectiveness of first-line pembrolizumab for advanced melanoma: A population-based study by the Canadian Real-world Evidence Value for Cancer Drugs (CanREValue) Collaboration.
Notice bibliographique
Résumé
17 Background: Randomized controlled trials (RCTs) demonstrate large survival benefits with anti-PD-1 checkpoint inhibitors compared to anti-CTLA4 therapy for advanced melanoma. However, it remains unclear if patients in routine practice derive a similar survival benefit or if real-world health utilization differs from trials. Outcomes are needed to inform life-cycle health technology reassessment (HTA) with real-world cost-effectiveness analysis. Methods: This study compared patients with advanced melanoma treated with publicly funded first-line ipilimumab (September 2012 - December 2014) or pembrolizumab (June 2016 - March 2018) in Ontario, Canada. These periods were chosen to reflect distinct eras of access to treatment. Linked administrative databases were used to identify cases, covariates, health-utilization and all-cause death. Inverse probability of treatment weighting (IPTW) with stabilizing weights was used to adjust for covariates (including: age, sex, melanoma site, rurality, income, comorbidity, stage at diagnosis, cancer history, prior brain metastasis treatment). Using a three-year time horizon, individual patient-level censoring-adjusted costs in 2019 Canadian dollars with a 1.5% annual discount rate were determined from the public payer’s perspective. The outcome was quality-adjusted life-years (QALY) measured at the individual patient level. Health utilities were based on accepted Canadian values from the initial HTA. The incremental cost-effectiveness ratio (ICER) was determined with bootstrap confidence intervals (CI). Results: Ninety patients treated with first-line ipilimumab, and 300 with pembrolizumab were identified. Those receiving pembrolizumab were older (median 70 vs.63 years), more likely to have multiple comorbidities (12% vs. 8%), and no prior brain radiation (83% vs. 74%). Covariates were balanced after weighting. Pembrolizumab was associated with improved OS (43.1% vs. 22.1% with ipilimumab at 3 years, IPTW adjusted hazard ratio: 0.52, 95% CI: 0.39-0.70; p < 0.001). Mean costs for pembrolizumab and ipilimumab were $212,706 (95% CI 196,122 - 229,290) and $158,352 ($143,218 - 173,484), and mean survival 1.20 QALY (95%CI 1.11 – 1.29) and 0.66 QALY (0.52 – 0.80) respectively. The ICER was $101,183/QALY (65,375 – 139,298). The probability of cost-effectiveness was 0%, 48% and 99% at willingness-to-pay thresholds of $50k, $100k and $150k respectively. Conclusions: In real-world patients, first-line pembrolizumab for advanced melanoma was associated with improved OS compared to ipilimumab. The real-world cost-effectiveness estimate of $101,183/QALY is similar to the model-based cost-effectiveness estimates ($114,389/QALY to $151,369/QALY) used in the initial health technology assessment recommendation prior to reimbursement.
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 | 0,004 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».