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Enregistrement W4405039315 · doi:10.1182/blood-2024-206375

A Real-World Comparison of CAR T-Cell Therapy Versus a Historical Standard-of-Care Approach for Relapsed-Refractory Large B-Cell Lymphoma in Ontario, Canada

2024· article· en· W4405039315 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 subventionnairesIpsenEisaiBeiGeneAstraZenecaEli Lilly and Company
Mots-clésRefractory (planetary science)MedicineLymphomaStandard of careChemotherapy regimenOncologyInternal medicineChemotherapyBiology

Résumé

récupéré en direct d'OpenAlex

Background Anti-CD19 Chimeric Antigen Receptor T-cell (CAR-T) immunotherapies have been funded in Canada for patients with relapsed-refractory large B-cell lymphoma (RR LBCL) after two lines of systemic therapy since December 2019. However, real-world evidence of CAR-T outcomes has been limited to small series with little comparison to prior standard-of-care management. We compared overall survival (OS), adverse events, and healthcare utilization for a cohort of patients with RR LBCL consecutively treated with CAR-T versus a cohort of historical controls treated with standard-of-care therapy prior to CAR-T approval. Methods This is a propensity-weighted retrospective cohort study of patients with RR LBCL treated at Princess Margaret (PM) Cancer Centre. Using linked clinical and administrative datasets, consecutive patients treated with CAR-T (2020-2022) following provincial funding approval were compared to a matched cohort of historical controls (2012-2017). Patients were followed from index date, defined as the date of progression following 2 lines of chemotherapy (2L) in the historical controls and following last therapy (2L or higher) in the CAR-T patients for up to 3-years, with maximum follow-up to March 31, 2023. Stabilized inverse probability treatment weighting (sIPTW) was used to account for confounding between cohorts (age, sex, lactate dehydrogenase, and comorbidities). Kaplan meier curves and IPTW-weighted Cox proportional hazard regression analyses estimated the adjusted hazard ratio (HR) between treatment cohort and OS. A landmark survival analysis of patients alive at 3 months post-index date addressed immortal time bias. Adverse events (AEs) from inpatient/emergency department [ED] diagnoses and healthcare utilization were reported per 1000 person-days at risk. Results A total of 86 CAR-T patients and 150 historical control patients were evaluable for comparison. Variables were balanced after applying the sIPTW (based on standardized difference <0.1); mean age was 56 years and males comprised 61%. Prior treatment included ASCT in 27.6% CAR-T vs 38.4% historical control patients (standardized difference 0.21; p=0.09). Post-2L progression, 58% of historical controls had no further treatment, 32% received intravenous or oral chemotherapy/targeted agents, 6.2% had an autologous stem cell transplant, and 10% received palliative chemotherapy and/or radiotherapy. CAR-T patients received tisagenlecleucel (33.3%) and axicabtagene ciloleucel (66.7%) CAR-T products. The OS probabilities at 1-, 2-, and 3-years were 68% (95% CI 53-79%), 60% (95% CI 44-73%), and 57% (95% CI 39-71%), respectively, in the CAR-T group, and 18% (95% CI 12-25%), 11% (95% CI 7-17%), and 10% (95% CI 5-16%), respectively, in the control group. The IPTW-adjusted HR for all-cause death was 0.22 (95% CI 0.15-0.33), and landmark survival analysis for all-cause death 3-months post-index date to end of follow-up generated a similar HR of 0.28 (CI 0.19-0.44) in the CAR-T group. CAR-T patients had a lower number of days hospitalized (77.73 [95% CI 75.00-80.57] vs 86.11 [95% CI 83.12-89.21] per 1000 person-day; p<0.001), ICU admissions (0.55 [95% CI 0.36-0.84] vs 1.26 [95% CI 0.94-1.69] per 1000 person-day; p=0.001), and ED visits (4.79 [95% CI 4.10-5.61] vs 2.07 [95% CI 1.65-2.60] per 1000 person-day; p<0.001). Additionally, CAR-T patients had lower events per 1000 person-days of: infection (1.44 [95% CI 1.10-1.87] vs 3.02 [95% CI 2.50-3.64] p<0.001), neutropenia (0.65 [95% CI 0.44-0.96] vs 1.79 [95% CI 1.4-2.29]; p<0.001), febrile neutropenia (0.45 [95% CI0.28-0.72] vs 1.47 [95% CI 1.12-1.92]; p<0.001), gastrointestinal toxicity (0.26 [95% CI 0.14-0.49] vs 0.69 [95% CI 0.46-1.02]), and respiratory infections (0.51 [95% CI 0.33-0.79] vs 0.91 [95% CI 0.65-1.29]; p=0.04). Conclusions CAR T-cell therapy produced a significant and sustained survival benefit versus historical standard-of-care management, with fewer hospitalizations and infections. Despite well-described CAR-T toxicities, historical control patients had more AEs, underscoring the lack of other effective salvage treatments. This study describes one of the largest real-world comparisons of patients with RR LBCL receiving CAR T-cell therapy compared to previous standard-of-care therapies and demonstrates its effectiveness amongst a broad cohort of eligible patients, consistent with the results of pivotal trials.

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)0,002
score de la tête « metaresearch » (Gemma)0,006
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 enseignants0,065
Score d'incertitude au seuil0,473

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,006
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,001
Communication savante0,0010,000
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 Opus0,038
Tête enseignante GPT0,306
Écart entre enseignants0,268 · 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

Citations2
Publié2024
Routes d'admission2
Résumé présentoui

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