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Enregistrement W4405048123 · doi:10.1182/blood-2024-210635

Patients with Poor Functional Status at Intake Experience Early Failure of CAR T-Cell Therapy for Third Line Treatment of RR-LBCL

2024· article· en· W4405048123 sur OpenAlexaffabout
Sita Bhella, Katrina Hueniken, Rachel Aitken, Carmel Waldron, Michael Crump, John Kuruvilla, Anca Prica, Vishal Kukreti, Robert Kridel, Abi Vijenthira, Chloe Yang, Richard Tsang, David Hodgson, Danielle Rodin, Nauman Malik, Woodrow Wells, Christine I. Chen

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueCAR-T cell therapy research
Établissements canadiensPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineCartPopulationInternal medicineSalvage therapyCohortUnivariate analysisRetrospective cohort studySurgeryMultivariate analysisChemotherapy

Résumé

récupéré en direct d'OpenAlex

Background: Princess Margaret (PM) is the referral centre for antiCD19 CAR T-cell therapy (CART) for a large regional population and currently treats patients from other provinces in Canada. Better understanding of early CART failure may inform selection criteria. Purpose: We evaluated outcomes of all patients referred for CART and explored risk factors for early failure, as defined by failure to receive cells, death within 100 days of infusion or progressive disease (PD) prior to or at day 100 response assessment. Methods: This is a single-centre retrospective review of consecutive adult patients with RR-LBCL referred for CART at PM from April 2020-November 2023 for > 3rd line therapy. Outcomes included progression-free survival (PFS) defined from date of cell infusion/ date of intake (for pts that failed to proceed with CART (PFPC)) to PD/death/last follow-up. Overall survival (OS) defined from date of cell infusion/date of intake (for PFPC) to death/last follow-up. To identify predictors for early failure, a univariate analysis examining the early failure and non-early failure cohort was conducted. Variables examined included: age, stage, ECOG, presence of bulky disease (>7 cm), relapsed vs. refractory, lymphoma subtype, cell of origin, presence of double hit or triple hit lymphoma, and failure to undergo ASCT. Metrics to infusion were examined including dates of CT demonstrating progression post 2L+ therapy, intake, apheresis and infusion. Results: 263 pts were referred for CART during the study period. 192 underwent CART (tisa-cel 47, axi-cel 145) and 71 were referred but did not undergo CART. Of these 71, 14 were found to be ineligible for CART at intake and were excluded. ITT analysis included 57 pts who did not receive CART. For the 57 pts who did not proceed with CART, reasons for not proceeding were identified in 56. Reasons included: patient factors (choice 12(21%), poor functional status 7(13%)), product factors (collection 2(4%), manufacturing 5(9%) and disease factors (progression 22(39%), active CNS disease 5(9%), death 3(5%)). 52% did not proceed with apheresis. Median time from date of progression noted on CT to intake appt was 19 days for tisa-cel (0-177) and 16.5 days for axi-cel (0-113). Median time from date of progression noted on CT to infusion was 50 days (19-100) for tisa-cel and 44 days (28-89) for axi-cel. Median time from apheresis to infusion was 43 days (35-107) for tisa-cel and 33 days (27-74) for axi-cel. There were no significant differences in median days from progression noted on CT to intake or referral to intake between early failure and non-early failure cohorts 15 v. 18 (p=0.603) and 10 v. 8.5 (p=0.128). Response at 100 days post CART was assessed in 192 pts. 83 achieved CR/CMR (43%), 25 achieved PR (13%), 64 (34%) experienced progression, and 2(1%) died before 100 days from toxicity (ICH, frailty post ICU for ICANS); and 100-day status was unknown/pending in 18(9%) patients and were censored. Median follow up time for all patients receiving CART was 12.02 mos (6.28-17.38) from infusion to censored. Median OS for the cohort receiving CART was not reached. 12-month OS for whole CART cohort, tisa-cel and axi-cel cohorts respectively were 66.9% (95% CI 58.9,76), 55.9% (95% CI 42.3, 73.7) and 72.8% (95% CI 63.7,83.2). Median PFS for all infused patients was 8.2 mos (95% CI 1.28, NYR). Median OS for the ITT cohort (CART and no CART) was 57.7 months (95% CI 50.5, 65.8) from intake date with median follow up 13.44 mos (95% CI 7.79,18.5). Median OS for the CART and no CART cohort was 68.8 mos (95% CI, 60.9,77.6) and 12.4 mos (95% CI 5.3, 28.9). A univariate analysis of predictors for early failure was conducted. Those with unknown status at Day 100 were excluded. 234 referred pts were included for analysis and 121(52%) pts met the definition of early failure. Of those who experienced early failure post CART, 62 pts (97%) experienced relapse and 2 pts (3%) died from toxicity. ECOG 2+ at intake (p=0.011) was identified as a predictor. Refractory disease (p=0.056) and presence of double /triple hit lymphoma (p=0.059) trended close to significance. Conclusions: We present the early experience with SOC CART for RR-DLBCL from a large tertiary Canadian centre. Limited RW cohorts have provided ITT results. A large proportion of referred patients experienced early failure, with 23% not receiving CART and 52% experiencing early failure. Novel strategies are required to better outcomes in those at risk of early failure.

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)0,001
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 enseignants0,003
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,024
Tête enseignante GPT0,282
Écart entre enseignants0,258 · 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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