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Enregistrement W4405039623 · doi:10.1182/blood-2024-201539

Real-World Comparison of Healthcare Costs and Resource Utilization Among Patients with Relapsed-Refractory Large B-Cell Lymphoma Treated with CAR T-Cell Therapy Versus Historical Standard-of-Care: A Cost-Consequence Analysis in Ontario, Canada

2024· article· en· W4405039623 sur OpenAlexaffabout
Tiana Kordbacheh, Anca Prica, Kelvin Chan, Mahmood AminiLari, Zharmaine Ante, Ning Liu, Inna Y. Gong, Sita Bhella, Michael Crump, Abi Vijenthira, John Kuruvilla, Robert Kridel, Christine I. Chen, Vishal Kukreti, Chloe Yang, Nauman Malik, David Hodgson, Danielle Rodin

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueCAR-T cell therapy research
Établissements canadiensSunnybrook Health Science CentreUniversity of TorontoPrincess Margaret Cancer CentreHealth Sciences CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineRefractory (planetary science)Standard of careHealth careLymphomaInternal medicineEconomic growthEconomics

Résumé

récupéré en direct d'OpenAlex

Background Chimeric Antigen Receptor T-cell therapy (CAR-T) has transformed the management of relapsed-refractory large B-cell lymphoma (RR LBCL) by offering the potential for long-term survival to patients who have exhausted other curative intent treatment. In 2019, the Canadian Agency for Drugs and Technologies in Health recommended funding CAR-T for patients with RR LBCL progressing after two or more lines of systemic therapy. However, CAR-T is resource-intensive to deliver and is associated with significant toxicity and health resource utilization. Real world data on healthcare spending associated with CAR-T is required to assist decision-makers and ensure its efficient and equitable delivery. We compared healthcare costs among a cohort of patients receiving CAR-T with a cohort of historical patients treated prior to CAR-T approval at Princess Margaret (PM) Cancer Centre in Toronto, Canada. Methods Using linked, institutional and population-based clinical and administrative databases in Ontario, Canada, patients with RR LBCL consecutively treated at PM with CAR-T (2020-2022) were compared to a historical PM control cohort of RR LBCL patients treated prior to CAR-T approval (2012-2017). Patients were followed from the date of progression following 2 lines of chemotherapy (2L) in the historical controls and date of progression after last therapy (2L or higher) prior to receiving CAR-T for up to 3-years, with maximum follow-up to March 31, 2023. Stabilized inverse probability of treatment weighting (sIPTW) was used to balance baseline covariates between the cohorts (age, sex, lactate dehydrogenase, and comorbidities). sIPTW-weighted Kaplan-Meier curves and Cox proportional hazard regression were used to estimate OS probability and hazard ratios (HR) for CAR-T patients versus historical controls. Generalized linear regression modelling was used to estimate total and resource-specific healthcare costs (2024 Canadian dollars), including mean 3-year incremental costs between the two arms (excluding CAR-T drug cost to focus on healthcare resource expenses [Axi-cel $485,021; Tisa-cel $450,000]). Costs were adjusted for censoring using inverse probability of censoring weighting (IPCW). Results Cohorts of 86 CAR-T-treated patients and 150 historical control patients were evaluated. After applying sIPTW, baseline variables were balanced between the two groups: mean age was 56 years and males comprised 61%. The 3-year OS probability was 57% (95% CI 39-71%) in the CAR-T group and 10% (95% CI 5-16%) in the historical control group, with an IPTW-adjusted HR of 0.22 (95% CI 0.15-0.33) for all-cause death. IPCW-adjusted 3-year mean [standard deviation (SD)] total healthcare cost per CAR-T patient was $141,870 [$125,251] vs $55,388 [$40,833] in historical controls (p<0.001), resulting in a mean 3-year incremental total healthcare cost of $86,482 (95% CI $64,422-108,542) in the CAR-T cohort. The majority of healthcare spending in both cohorts was incurred through inpatient days (42% of CAR-T total expenditure vs 44% in historical controls). CAR-T patients incurred a mean 3-year incremental inpatient cost of $34,720 [95% CI $22,625-46,816], which represented 40% of the incremental total healthcare cost for CAR-T patients. The CAR-T cohort also had significantly higher mean 3-year incremental healthcare resource costs than historical control patients in: ambulatory cancer clinics ($14,663 [95% CI $9,609-19,717]; 17% of incremental total healthcare cost), outpatient clinic visits ($11,782 [95% CI $9,122-14,442]; 14%), physician costs ($8718 [95% CI $5,913-11,523]; 10%), oral drug costs ($7,676 [95% CI $2,605-12,747]; 9%), and systemic chemotherapy drug costs ($4,729 [95% CI $1,435-8,022]; 5%). Conclusion In this real-world analysis, CAR-T therapy was associated with improved survival as well as higher healthcare costs compared to patients treated with historical standard-of-care therapies. Greater inpatient care needs amongst the CAR-T cohort were a significant contributor to the higher overall spending observed, followed by clinic, physician, and additional drug costs. These data provide important considerations for funders and decision-makers in determining the value of CAR-T therapy in Ontario. These cost parameters can also inform future economic modelling of CAR-T therapy.

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)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,067
Score d'incertitude au seuil0,485

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0020,008
Études des sciences et des technologies0,0020,001
Communication savante0,0020,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,025
Tête enseignante GPT0,288
Écart entre enseignants0,263 · 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'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

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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