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Enregistrement W3213746728 · doi:10.1182/blood-2021-147568

Novel Agents May be Preferable to Chemotherapy for Large B-Cell Lymphoma Progressing after CD19-CAR-T: A Multicenter Observational Study

2021· article· en· W3213746728 sur OpenAlexaff
Ana Alarcón Tomás, Joshua Fein, Shalev Fried, Warren Fingrut, Theodora Anagnostou, Anna Alperovich, Nishi Shah, Ellen Fraint, Richard J. Lin, Michael Scordo, Aishat Olaide Afuye, Connie Lee Batlevi, Michal J. Besser, Parastoo B. Dahi, Ivetta Danylesko, Sergio Giralt, Brandon S. Imber, Arnon Nagler, M. Lia Palomba, Gilles Salles, Craig S. Sauter, Gunjan L. Shah, Noga Shem‐Tov, Avichai Shimoni, Joachim Yahalom, Ronit Yerushalmi, Abraham Avigdor, Miguel‐Angel Perales, Roni Shouval

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueCAR-T cell therapy research
Établissements canadiensStem Cell Network
Organismes subventionnairesnon disponible
Mots-clésMedicineInterquartile rangeInternal medicineCAR T-cell therapyCumulative incidencePopulationCohortOncologyCytokine release syndromeMinimal residual diseaseLymphomaCancerChimeric antigen receptorImmunotherapyLeukemia

Résumé

récupéré en direct d'OpenAlex

Abstract Up to 70% of large B-cell lymphoma (LBCL) patients will eventually experience relapse or progress following CD19-CAR-T therapy. Data guiding management of this challenging population are lacking. Therefore, we aimed to study the relationship between treatment strategies and outcomes following CD19-CAR-T failure. We included 273 adults, from two centers, treated with CD19-CAR-T (axicabtagene-ciloleucel [98, 36%], tisagenlecleucel [76, 28%], lisocabtagene-maraleucel [28, 10%], and an academic CD28-product [71, 26%]) for relapsed/refractory LBCL Cumulative incidence of relapse or progression was 40% (95% CI: 34%, 46%). Of 176 patients with residual or relapsed disease post-CAR-T (Fig. A), 133 received subsequent first-line anti-cancer therapy for active or residual disease (primary cohort) at a median of 79 days (interquartile range 49-124) after CAR-T infusion. Within the primary cohort, 65% of patients had stage III-IV disease at time of subsequent therapy. Most lymphomas remained CD19-positive after CAR-T therapy (45 biopsies, 91% positive by flow cytometry [58% normal, 33% dim expression]). At time of first treatment post-CAR-T, nearly all patients had either relapsed disease or stable/progressive disease (SD/PD), with eight patients in ongoing partial response (PR). With a median follow-up of 14.5 months (95% CI: 11.5-21.4), the median overall survival (OS) from time of first subsequent therapy was 8.6 months (IQR 6.9-12.0). We sought to identify determinants of survival among patients receiving initial post-CAR-T treatment. Variables measured pre- and post-CAR-T therapy and significantly associated (p < 0.1) with OS in univariable Cox regression were introduced into a multivariable model. Age ≥ 65y (HR 2.01 [95% CI: 1.23-3.29], p 0.005), bulky disease at apheresis (HR 2.05 [1.07-3.95], p 0.031), and disease refractory to CAR-T therapy (HR 1.89 [1.19-2.98], p 0.007) were associated with inferior OS in the multivariable analysis. Based on the cumulative burden of OS determinants, we propose a prognostic tool allowing risk stratification of patients receiving treatment post-CAR-T. Increasing number of these three risk factors was associated with greater mortality (HR 1.86 [1.32-2.62], p<0.001; Fig. B). Six-month OS ranged from 30% (95% CI: [16-57]) with ≥ 2 factors to 76% (64-91) with none. Therapy strategies post-CAR-T varied. Polatuzumab (n=25), anthracycline or platinum ("chemotherapy"; n=17), BTK inhibitors (n=13) and lenalidomide (n=12) based treatment were most frequently administered for non-localized disease (stage ≥2). Involved site radiation therapy (ISRT; n=20) was primarily given for stage I disease (Fig. C). Overall response rate (ORR) in the entire cohort was 47% (25% CR; 22% PR). Fig. D shows response rates by treatment. Remarkably, novel agents, including polatuzumab and lenalidomide-based therapies, had ORR of 52% (CR 35%) and 33% (CR 33%), respectively. In contrast, traditional chemotherapy-based approaches did not result in CR, and only 50% achieved PR. Survival was poorest with chemotherapy (6 month OS: 25% [95% CI: [11-59]), while rates with lenalidomide and polatuzumab-based therapies were 65% (42-100) and 67% (50-89). Patients and disease characteristics across treatment groups were unbalanced. However, the three prognostic factors comprising the OS prognostic tool: age ≥ 65y, bulky disease at apheresis and disease refractoriness to CAR-T, were similar across lenalidomide, polatuzumab, checkpoint inhibitors, and chemotherapy-based treatment groups. Patients who underwent alloHCT were significantly younger but achieved high rates of response. In conclusion, we present the most extensive and detailed experience of treatment outcomes post-CAR-T therapy. Our data suggest that novel agents may be preferable to traditional chemotherapies as the first post-CAR-T treatment. However, survival is still poor, and investigation of curative approaches is needed. We provide a tool to inform mortality risk in this difficult-to-treat population. Figure 1 Figure 1. Disclosures Scordo: i3 Health: Other: Speaker; Kite - A Gilead Company: Membership on an entity's Board of Directors or advisory committees; McKinsey & Company: Consultancy; Omeros Corporation: Consultancy; Angiocrine Bioscience: Consultancy, Research Funding. Batlevi: ADC Therapeutics: Consultancy; Juno/Celgene: Consultancy; Life Sciences: Consultancy; Regeneron: Current holder of individual stocks in a privately-held company; Karyopharm: Consultancy; Viatris: Current holder of individual stocks in a privately-held company; GLG Pharma: Consultancy; Xynomic: Research Funding; Seattle Genetics: Consultancy; Kite Pharma: Consultancy; TG Therapeutics: Consultancy; TouchIME: Honoraria; Memorial Sloan Kettering Cancer Center: Current Employment; Bayer: Research Funding; BMS: Current holder of individual stocks in a privately-held company; Medscape: Honoraria; Pfizer: Current holder of individual stocks in a privately-held company; Moderna: Current holder of individual stocks in a privately-held company; Dava Oncology: Honoraria; Roche/Genentech: Research Funding; Novartis: Research Funding; Epizyme: Research Funding; Janssen: Research Funding; Autolus: Research Funding. Dahi: Gilead sciences: Membership on an entity's Board of Directors or advisory committees; Kite pharma: Membership on an entity's Board of Directors or advisory committees. Giralt: PFIZER: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Actinnum: Membership on an entity's Board of Directors or advisory committees; SANOFI: Membership on an entity's Board of Directors or advisory committees; CELGENE: Membership on an entity's Board of Directors or advisory committees; AMGEN: Membership on an entity's Board of Directors or advisory committees; JANSENN: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; JAZZ: Membership on an entity's Board of Directors or advisory committees. Palomba: Pluto: Honoraria; Lygenesis: Honoraria; Magenta: Honoraria; Juno: Patents & Royalties; Wolters Kluwer: Patents & Royalties; WindMIL: Honoraria; Priothera: Honoraria; Nektar: Honoraria; Rheos: Honoraria; BeiGene: Consultancy; Seres: Honoraria, Other: Stock, Patents & Royalties, Research Funding; Kite: Consultancy; Ceramedix: Honoraria; Notch: Honoraria, Other: Stock; Novartis: Consultancy; PCYC: Consultancy. Salles: Ipsen: Consultancy; Regeneron: Consultancy, Honoraria; Genentech/Roche: Consultancy; Genmab: Consultancy; Takeda: Consultancy; Novartis: Consultancy; Incyte: Consultancy; Morphosys: Consultancy, Honoraria; Janssen: Consultancy; Epizyme: Consultancy, Honoraria; Allogene: Consultancy; Kite/Gilead: Consultancy; Loxo: Consultancy; Miltneiy: Consultancy; Debiopharm: Consultancy; Velosbio: Consultancy; Rapt: Consultancy; BMS/Celgene: Consultancy; Beigene: Consultancy; Abbvie: Consultancy, Honoraria; Bayer: Honoraria. Sauter: Genmab: Consultancy; Celgene: Consultancy, Research Funding; Gamida Cell: Consultancy; GSK: Consultancy; Bristol-Myers Squibb: Research Funding; Kite/Gilead: Consultancy; Precision Biosciences: Consultancy; Novartis: Consultancy; Spectrum Pharmaceuticals: Consultancy; Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding. Shah: Amgen: Research Funding; Janssen Pharmaceutica: Research Funding. Avigdor: Gilead: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; BMS: Research Funding; Janssen: Research Funding; Takeda: Consultancy, Honoraria. Perales: Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Equilium: Honoraria; Cidara: Honoraria; MorphoSys: Honoraria; Incyte: Honoraria, Other; Servier: Honoraria; Celgene: Honoraria; Medigene: Honoraria; Kite/Gilead: Honoraria, Other; Karyopharm: Honoraria; Nektar Therapeutics: Honoraria, Other; Merck: Honoraria; Novartis: Honoraria, Other; NexImmune: Honoraria; Miltenyi Biotec: Honoraria, Other; Omeros: Honoraria; Sellas Life Sciences: Honoraria. Shouval: Medexus: Consultancy.

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)0,004
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 seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,098
Tête enseignante GPT0,367
Écart entre enseignants0,269 · 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

Citations10
Publié2021
Routes d'admission1
Résumé présentoui

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