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Enregistrement W2977473977 · doi:10.1182/blood.v128.22.1186.1186

Bendamustine and Rituximab Versus Conventional Chemoimmunotherapy As a Frontline Treatment for Patients with Indolent B-Cell Lymphoma: A Cost-Effectiveness Analysis

2016· article· en· W2977473977 sur OpenAlexaffabout
Andrew Aw, Kathryn Coyle, Isabelle Bence‐Bruckler, Christopher Bredeson, Doug Coyle

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensUniversity of OttawaOttawa Hospital
Organismes subventionnairesnon disponible
Mots-clésChemoimmunotherapyMedicineRituximabOncologyRegimenInternal medicineBendamustineProgression-free survivalLymphomaChemotherapy

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Indolent lymphomas are characterized by a chronic relapsing-remitting course. Bendamustine-Rituximab (BR) has been shown to improve overall response rate and progression free survival (PFS) in the upfront treatment of patients with indolent B-cell non-Hodgkin lymphoma (iNHL), as compared with conventional chemoimmunotherapy (Rummel et al., 2013; Flinn et al., 2014). The pan-Canadian Oncology Drug Review has recommended publicly funding BR, but concluded there is substantial uncertainty regarding the regimen's cost-effectiveness. The objective of our study was to assess the cost-effectiveness of BR as compared with Rituximab-Cyclophosphamide, Doxorubicin, Vincristine, Prednisone (RCHOP) as frontline treatment for patients with advanced iNHL from a Canadian perspective. Methods: A Markov model was developed to estimate the costs, life expectancy and quality-adjusted life-years (QALYs) associated with the two regimen options allowing determination of the incremental cost-utility ratio (ICUR). Model parameters were derived from peer-reviewed studies. Key health states included FT (frontline therapy), MR (2-year state of maintenance R), PF1 (1st progression-free state), PD1/2/3 (subsequent progressive disease states requiring salvage), PF2/3/4 (subsequent progression-free states post-salvage), palliation and death. To determine progression after FT, individual data elements were derived from the published literature, and transition probabilities were determined through parametric survival analysis. Age-related mortality was obtained from Statistics Canada. Cost data (in 2016 Canadian dollars) were obtained from current funding arrangements under the New Drug Funding Program of Cancer Care Ontario, the Ontario Health Insurance Plan Schedule of Benefits and Fees, and the published literature. Utility values for health states and utility decrements associated with treatment related adverse events (AEs) were derived from peer-reviewed studies. The analysis was performed from the health care provider perspective, with a lifetime time horizon (equivalent to 24 years) and cycle lengths of 6 months. Patients were treated with a maximum of 3 lines of salvage therapy (3rd salvage permitted in age-appropriate patients achieving at least 1 year remission from 2nd line salvage). In order to address uncertainty of model input variables, a probabilistic analysis in which model inputs were represented by probability distributions was utilized, permitting a Monte Carlo simulation with 5000 replications. Costs and utilities were discounted at a rate of 5% per annum. Subgroup analyses for the following iNHL histologies were performed using individualized parametric survival curves: follicular lymphoma (FL), mantle cell lymphoma (MCL), marginal zone lymphoma (MZL), lymphoplasmacytic lymphoma (LPL). Results: The average costs and QALYs for the two treatment strategies were as follows: $116,811 and 5.86 QALYs for RCHOP; $121,364 and 6.38 QALYs for BR. The incremental cost per QALY gained for using BR with respect to RCHOP was $8,812 (Figure 1). Subgroup analyses revealed robust ICUR results: $27,398 (FL), $8,924 (MCL), $10,012 (MZL), $6,565 (LPL). For the commonly accepted willingness to pay threshold (WTP) of $50,000 per QALY, BR was the more cost-effective strategy 92% of the time in the entire cohort (Figure 2). In the subgroup analyses, BR was the more cost-effective strategy 66%, 82%, 64%, 86% of the time in FL, MCL, MZL, LPL respectively. ICUR results were robust to sensitivity analyses of key variables including age at study entry, maximum allowable age for therapy, duration of AEs, probability of death from palliation state and discount rate. Conclusion: Our model suggests that BR is a cost-effective strategy for the frontline treatment of patients with iNHL as compared with RCHOP. The cost-effectiveness of BR may be driven by the upfront PFS advantage despite higher acquisition costs and is consistent in various iNHL histology subgroups. Our analysis supports the use of frontline BR for iNHL in the Canadian setting. Figure 1 Cost-effectiveness acceptability curve Figure 1. Cost-effectiveness acceptability curve Figure 2 Incremental cost-effectiveness of BR relative to RCHOP with WTP threshold of $50,000 per QALY Figure 2. Incremental cost-effectiveness of BR relative to RCHOP with WTP threshold of $50,000 per QALY Disclosures Bence-Bruckler: Lundbeck: Membership on an entity's Board of Directors or advisory committees.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,295
Score d'incertitude au seuil0,586

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,010
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,005
Bibliométrie0,0020,002
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

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 Opus0,016
Tête enseignante GPT0,273
Écart entre enseignants0,257 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai non randomisé
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

Citations4
Publié2016
Routes d'admission2
Résumé présentoui

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