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Enregistrement W3217363670 · doi:10.1182/blood-2021-146237

Cost per Responder Analysis to Assess the Value of CAR-T Therapy for Relapsed or Refractory Multiple Myeloma

2021· article· en· W3217363670 sur OpenAlexaff
Thomas Martin, Saad Z. Usmani, N.R. Joseph, Concetta Crivera, Satish Valluri, Carolyn C. Jackson, Lucas Cohen, Sumeet Singh, Sundar Jagannath

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueCAR-T cell therapy research
Établissements canadiensEVERSANA (Canada)
Organismes subventionnairesnon disponible
Mots-clésMedicineMultiple myelomaOncologyClinical trialInternal medicineChimeric antigen receptorCost effectivenessImmunotherapyCancer

Résumé

récupéré en direct d'OpenAlex

Abstract New classes of therapies have emerged for treating Relapsed or Refractory Multiple Myeloma (RRMM) patients, including chimeric antigen receptor T-cell (CAR-T) therapies targeting the B-cell maturation antigen. While CAR-T therapies are expected to be a more expensive class of treatment compared to chemotherapy, 1 they have been shown to have a high overall response rate (ORR) and progression-free survival (PFS). 2,3 As newer, more innovative RRMM therapies are developed and brought to market, payers will need to balance their higher efficacy and total treatment costs when assessing potential value. To assess the value of RRMM CAR-T therapies (ciltacabtagene autoleucel [cilta-cel] and idecabtagene vicleucel [ide-cel]), we developed a cost per responder (CPR) model that incorporates efficacy and total cost of treatment. In the absence of head-to-head trial data for CAR-T therapies, indirect treatment comparisons (ITCs) can be used to evaluate comparative efficacy, and the results can be used to inform a CPR model. Matching-adjusted indirect comparisons (MAIC) is a form of ITC that involves matching and adjusting a treatment group from a clinical study with individual patient-level data (IPD) available to a comparator for which only summary-level data are available. This method mitigates potential bias arising from differences in patient characteristics between trials and is widely used and accepted in comparative effectiveness research. Unanchored matching adjusted indirect comparison (MAIC) analyses were used to inform the comparative efficacy of cilta-cel versus ide-cel in our CPR model. MAIC results indicated that cilta-cel was associated with statistically significantly improved ORR (odds ratio [OR]: 87.99 [95% confidence interval [CI]: 20.32, 381.01; p < .0001]), complete response or better (≥CR) rate (OR: 5.96 [95% CI: 2.76, 12.88; p < .0001]) and PFS (hazard ratio [HR]: 0.36 [95% CI: 0.22, 0.59; p < .0001]) when compared with ide-cel. 4 To adequately capture total treatment costs for each treatment of interest, CPR models should include all costs related to acquisition and delivery of treatment. Relevant costs of CAR-T therapy for RRMM include the cost of apheresis, bridging therapy, costs of CAR-T acquisition and administration, supportive care and monitoring costs, adverse event management costs, and any costs associated with delivery of inpatient or outpatient clinical services. Preliminary results of the CPR analysis indicate that ide-cel is associated with a cost per ORR of approximately $743,000, a cost per CR or better of $1.66 million and a cost per month in PFS of approximately $55,000. Corresponding results for cilta-cel will be generated after the PDUFA date (November 29, 2021), and presented at ASH 2021. In conclusion, CPR models have significant potential to assist payers in evaluating the value of newer, more innovative RRMM therapies by integrating information on both total costs and efficacy. References 1 Pagliarulo N. FDA approves first CAR-T cell therapy for multiple myeloma. https://www.biopharmadive.com/news/fda-car-t-multiple-myeloma-approval-bristol-myersbluebird/597438/#:~:text=The%20pharma%2C%20which%20licensed%20the,other%20approve d%20CAR%2DT%20therapies. Published 27 March 2021. Accessed 22 June 2021. 2 Munshi NC, Anderson Jr LD, Shah N, et al. Idecabtagene vicleucel in relapsed and refractory multiple myeloma. N Engl J Med. 2021;384(8):705-16. 3 Madduri D, Berdeja JG, Usmani SZ, et al. CARTITUDE-1: phase 1b/2 study of ciltacabtagene autoleucel, a B-cell maturation antigen-directed chimeric antigen receptor T-cell therapy, in relapsed/refractory multiple myeloma [abstract]. Blood. 2020;136(1 supplement). Abstract 177. 4 Martin T, Usmani SZ, Schecter JM, Vogel M, Jackson CC et al. (2021) Matching-adjusted indirect comparison of efficacy outcomes for ciltacabtagene autoleucel in CARTITUDE-1 versus idecabtagene vicleucel in KarMMa for the treatment of patients with relapsed or refractory multiple myeloma. Curr Med Res Opin 1-10. Disclosures Martin: Sanofi: Research Funding; Oncopeptides: Consultancy; Janssen: Research Funding; Amgen: Research Funding; GlaxoSmithKline: Consultancy. Usmani: Pharmacyclics: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Merck: Consultancy, Research Funding; SkylineDX: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding; Takeda: Consultancy, Research Funding, Speakers Bureau; Janssen Oncology: Consultancy, Research Funding; Abbvie: Consultancy; Array BioPharma: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding, Speakers Bureau; Celgene/BMS: Consultancy, Research Funding, Speakers Bureau; GSK: Consultancy, Research Funding; EdoPharma: Consultancy; Janssen: Consultancy, Research Funding, Speakers Bureau; Amgen: Consultancy, Research Funding, Speakers Bureau. Joseph: Johnson and Johnson: Current Employment, Current equity holder in publicly-traded company. Crivera: Johnson & Johnson: Current Employment, Current equity holder in publicly-traded company. Valluri: Janssen: Current Employment, Current equity holder in publicly-traded company. Jackson: Memorial Sloan Kettering Cancer Center: Consultancy; Janssen: Current Employment. Cohen: Eversana Life Science Services: Current Employment, Other: Eversana Life Science Services was contracted by Janssen to work on this project.. Singh: Eversana Life Science Services: Current Employment, Other: Eversana Life Science Services was contracted by Janssen to work on this project..

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)0,020
score de la tête « metaresearch » (Gemma)0,036
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,106

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0200,036
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,007
Bibliométrie0,0030,002
Études des sciences et des technologies0,0000,001
Communication savante0,0020,002
Science ouverte0,0030,002
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0090,001

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 Opus0,091
Tête enseignante GPT0,378
Écart entre enseignants0,287 · 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
Publié2021
Routes d'admission1
Résumé présentoui

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