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Enregistrement W3212362631 · doi:10.1182/blood-2021-151701

Are Novel Therapies Worth the Cost for Young Patients?: A Cost-Effectiveness Analysis of Frontline Therapies with or without Radiation for Early-Stage Unfavourable Hodgkin Lymphoma

2021· article· en· W3212362631 sur OpenAlexaffabout
Abi Vijenthira, David Hodgson, Matthew C. Cheung, Michael Crump, Anca Prica

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueHealth Systems, Economic Evaluations, Quality of Life
Établissements canadiensSunnybrook Health Science CentreHealth Sciences CentreUniversity Health NetworkPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicinePopulationRadiation therapyCost-effectiveness analysisBreast cancerCost effectivenessOncologyCancerIntensive care medicineInternal medicineRisk analysis (engineering)Environmental health

Résumé

récupéré en direct d'OpenAlex

Abstract Background: A variety of frontline treatment regimens exist for early-stage unfavourable Hodgkin lymphoma (HL), offering personalization of risk versus benefit in this primarily young population of patients. While radiation therapy has been a mainstay of treatment due to improved progression-free survival (PFS), recent studies have challenged this paradigm, using a PET-driven approach (HD17) or incorporating novel agents (nivolumab-AVD (N-AVD), brentuximab-AVD (A-AVD)). Long term risks of radiation and chemotherapy include secondary breast and other cancers, and heart failure; however novel regimens are more costly with uncertainty surrounding long-term efficacy. Methods: A cost-effectiveness and cost-utility analysis was conducted to compare five published frontline approaches for early-stage unfavourable HL: HD17, two H10 approaches, N-AVD, and A-AVD without radiation (Table 1). A Markov model was constructed with a lifetime horizon using TreeAge Pro 2021 (Figure 1). The base case was a 20-year-old female with a mediastinal mass who would require chest field radiation. Baseline estimates in the model were derived from the literature, including risk of relapse after each line of therapy, risk of late complications (breast cancer, secondary cancer, and/or heart failure), risk of death (from complications, lymphoma, and background mortality), and health state utilities. A Canadian public health care payer's perspective was taken, and costs are estimated in 2021 Canadian dollars. Global discounting of 3% was used. Results: Probabilistic sensitivity analyses were performed (10,000 simulations). First, we evaluated the uncertainty of long-term PFS using novel regimens (N-AVD or A-AVD); at a willingness-to-pay of $50,000/QALY, N-AVD was the most cost-effective regimen when 5-year PFS was at least 92% (Table 2). If 5-year PFS with N-AVD was <92%, HD17 became the most cost-effective approach. There was no PFS threshold at which A-AVD was the most cost-effective regimen. Holding the 5-year PFS of novel regimens at 92%, the model remained robust to multiple deterministic sensitivity analyses testing key variables including health state utilities (of relapse post-transplant, breast cancer, second malignancy, heart failure), costs (of radiation, autologous stem cell transplant, breast cancer, second malignancy, heart failure), and risks (of breast cancer after radiation, cardiovascular disease after radiation and/or chemotherapy,). However, if the risk of developing second cancer was less than 2% after 5 years with HD17 approach (current estimates 1% at 48 months in HD17 to 2% at 43 months in HD14 (which used a similar regimen)), or if the median overall survival after secondary cancer was over 9 years, HD17 became the most cost-effective regimen. The threshold cost for brentuximab to make A-AVD the most cost-effective regimen was <$5000 per dose (current price $14,520 CAD). Conclusions: If the long term PFS of nivolumab-AVD is greater than 92%, it could be the most cost-effective regimen when treating a young female patient with early-stage unfavourable Hodgkin lymphoma. This model accounts for increased costs with nivolumab added to chemotherapy, due to potential reduced incidence of late effects. However, there remain uncertainties in efficacy and risk regarding novel therapies as only non-randomized Phase II studies with short follow-up durations have been published; further trials of these approaches are being planned. HD17 remains the most cost-effective approach among published Phase III regimens. Long term follow-up of HD17 will also be meaningful to understand the risk of second cancer with this approach, which may impact its cost-effectiveness. Figure 1 Figure 1. Disclosures Crump: Epizyme: Research Funding; Kyte/Gilead: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Roche: Research Funding. Prica: Astra-Zeneca: Honoraria; Kite Gilead: Honoraria.

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)0,008
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,042

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,013
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,006
Bibliométrie0,0020,001
Études des sciences et des technologies0,0000,001
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

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 Opus0,202
Tête enseignante GPT0,383
Écart entre enseignants0,181 · 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'étudeSimulation ou modélisation
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

Citations0
Publié2021
Routes d'admission2
Résumé présentoui

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