Multivariable Modeling of Disease and Treatment Characteristics of Adults with B-ALL in MRD-Negative CR after CD19 CAR-T Cells Identifies Factors Impacting Disease-Free Survival
Notice bibliographique
Résumé
Abstract Introduction Autologous T cells expressing a CD19-specific chimeric antigen receptor (CAR) have produced impressive minimal residual disease-negative complete remission (MRD-neg CR) rates in relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL) patients (pts). Factors associated with durable remission in pts achieving MRD-neg CR after immunotherapy with T cells engineered with a CD19 CAR (FMC63.41bb.3ζ) have not been elucidated. Methods We studied factors impacting disease-free survival (DFS) of adults with B-ALL treated with lymphodepletion chemotherapy and CD19 CAR-T cells in a phase I/II clinical trial (NCT01865617). Pts were eligible for this analysis if they had bone marrow leukemia identified by flow cytometry and/or extramedullary disease before CAR-T cell therapy, and received CAR-T cells at or below the previously determined maximum tolerated dose (MTD; Turtle, JCI 2016). Anti-tumor response after CAR-T cell infusion was assessed by bone marrow aspiration and biopsy, with PET-CT performed in pts with extramedullary disease. High resolution (1:10,000) flow cytometry was used to identify marrow MRD, and marrow from pts in MRD-neg CR was evaluated by high throughput sequencing (HTS) of IGH, IGK, TRB, TRD, and TRG genes. Cox regression univariate and stepwise multivariable modeling were performed to identify factors associated with DFS. Results Of 57 pts who received lymphodepletion and CD19 CAR-T cells, 53 were evaluable for response and 4 were not evaluable (one MRD-neg CR before CAR-T cell infusion; 2 received CAR-T cells above the MTD; one fatal neurotoxicity prior to restaging). Forty-five of 53 restaged pts (85%) achieved MRD-neg CR after CAR-T cell therapy. With a median follow-up of 30.9 months, DFS and overall survival (OS) were longer in pts who achieved MRD-neg CR compared to those who did not (Fig 1A; median DFS, 7.6 vs 0.8 months, P < .0001; median OS, 20.0 vs 5.0 months, P = .014). Twenty-eight of the 45 pts who achieved MRD-neg CR had a leukemic clone identified by HTS prior to CAR-T cell infusion, and in 20 of these pts (71%), the leukemic clone was not detected in marrow 3 weeks after CAR-T cell infusion. DFS was better in MRD-neg CR pts with no detected malignant clone compared to those with a persistent clone by HTS (Fig 1B; median DFS, 8.4 vs 3.6 months, P = .036). We then used stepwise multivariable modeling to determine factors impacting DFS in the pts who achieved MRD-neg CR (n = 45). Better DFS was seen in pts with a higher pre-lymphodepletion platelet count (hazard ratio, HR 0.65 [95% CI; 0.47-0.88] per 50,000/μL increment P = .006), lower pre-lymphodepletion LDH (HR 1.39 [1.12-1.74] per 100 U/L increment, P = .003), and with incorporation of fludarabine into the cyclophosphamide-based lymphodepletion (Cy/Flu; HR 0.34 [0.15-0.78], P = .011). Similar findings were noted in analysis of MRD-neg CR pts who had no malignant clone by HTS after CAR-T cells. Pts with platelets ≥100,000/μL and normal LDH before lymphodepletion who received Cy/Flu (good risk, n = 15) had 2-year point estimates of DFS and OS of 78% and 86%, respectively. Allogeneic hematopoietic cell transplantation (HCT) is standard of care in suitable R/R adult B-ALL pts after achieving MRD-neg CR. Eighteen pts in MRD-neg CR after CAR-T cells underwent HCT a median of 2.3 months after CAR-T cell infusion. We analyzed the effect on DFS of HCT after CAR-T cell therapy by treating HCT as a time-dependent covariate. After adjusting for LDH, platelets, and Cy/Flu lymphodepletion, pts undergoing HCT after CAR-T cell therapy had lower risk of failure for DFS compared to those who did not undergo HCT (Table 1). No significant interaction effect was seen between HCT and risk group (P = .51). With a median follow-up of 28.4 months after HCT, 2-year point estimates of DFS and OS were 61% and 72% respectively. The 2-year cumulative incidence of relapse was 17% and non-relapse mortality was 23%. Conclusion A high rate of MRD-neg CR was seen following CD19 CAR-T cell therapy in adult B-ALL pts and is associated with improved DFS and OS. Absence of the index clone by HTS after CAR-T cells was associated with better DFS, suggesting deeper responses are associated with improved outcomes. Stepwise multivariable modeling identifies better DFS in pts with higher pre-lymphodepletion platelet count and lower LDH, and with use of Cy/Flu lymphodepletion. After adjusting for these factors, HCT after CD19 CAR-T cells may also be associated with better DFS. Disclosures Hay: DAVA Oncology: Honoraria. Hirayama:DAVA Oncology: Honoraria. Li:Juno Therapeutics: Employment, Equity Ownership. Till:Mustang Bio: Patents & Royalties, Research Funding. Kiem:Rocket Pharmaceuticals: Consultancy; Homology Medicine: Consultancy; Magenta: Consultancy. Ramos:Seattle Genetics: Employment, Equity Ownership. Shadman:Qilu Puget Sound Biotherapeutics: Consultancy; AstraZeneca: Consultancy; Pharmacyclics: Research Funding; Genentech: Consultancy; Mustang Biopharma: Research Funding; AbbVie: Consultancy; Celgene: Research Funding; Verastem: Consultancy; Acerta Pharma: Research Funding; Genentech: Research Funding; TG Therapeutics: Research Funding; Beigene: Research Funding; Gilead Sciences: Research Funding. Cassaday:Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Research Funding; Incyte: Research Funding; Seattle Genetics: Other: Spouse Employment, Research Funding; Jazz Pharmaceuticals: Consultancy; Kite Pharma: Research Funding; Pfizer: Consultancy, Research Funding; Merck: Research Funding. Acharya:Juno Therapeutics: Research Funding; Teva: Honoraria. Riddell:Adaptive Biotechnologies: Consultancy; NOHLA: Consultancy; Juno Therapeutics: Equity Ownership, Patents & Royalties, Research Funding; Cell Medica: Membership on an entity's Board of Directors or advisory committees. Maloney:Seattle Genetics: Honoraria; Roche/Genentech: Honoraria; GlaxoSmithKline: Research Funding; Janssen Scientific Affairs: Honoraria; Juno Therapeutics: Research Funding. Turtle:Adaptive Biotechnologies: Consultancy; Eureka Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Juno Therapeutics / Celgene: Consultancy, Patents & Royalties, Research Funding; Gilead: Consultancy; Nektar Therapeutics: Consultancy, Research Funding; Caribou Biosciences: Consultancy; Precision Biosciences: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Bluebird Bio: Consultancy; Aptevo: 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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».