Routine Pre-Apheresis Markers As Predictors for Efficacy and Safety Outcomes Following CD19 CAR-T Cell Therapy - a Single Center Experience
Notice bibliographique
Résumé
Background : CD19 CAR-T cell therapy is an effective therapy in the setting of relapsed or refractory large B cell lymphoma (LBCL). However, up to 50-60% of patients do not achieve a durable remission. Baseline biomarkers such as circulating CD3 count, total lymphocyte (ALC) and monocyte (AMC) count have recently emerged as potential predictors of response to CD19 CAR-T therapy in LBCL. However, the use of these markers in the real-world setting has not been validated. Our aim was to evaluate if routine baseline pre-apheresis data predict 100 day response and early immune mediated toxicities. Methods : Retrospective chart review was performed. All patients who received anti-CD19 CAR-T cell therapy (Axi-cel or Tisa-cel) for the indication of LBCL at the Princess Margaret Cancer Center, in Toronto, Canada from June 2020 to April 2024 were screened. Patients who had baseline peripheral values drawn at the time of apheresis, successful CAR-T infusion, and day 100 disease assessment were included in the final analysis. 17 patients, who experienced treatment or disease related deaths prior to day 100 assessment, were excluded. Statistical analysis using Wilcoxon rank-sum and Kruskal-Wallis tests were applied. Responders were defined as achieving complete metabolic response (CMR) or partial metabolic response (PMR), and non-responders as progressive metabolic disease (PMD) or stable metabolic disease (SMD) based on the Lugano Criteria by PET scan. Results : A total of 159 patients were included in the analysis. 121(38%) patients received Axi-cel and 38(24%) Tisa-cel. The median age was 61 years (range: 19-83), 58% had refractory and 42% relapsed disease. 30% had received a prior autologous stem cell transplant and 73% required bridging therapy (steroids 9%, chemo alone 25%, radiotherapy 23%, and combination 16%). Peripherally drawn pre-apheresis markers, including median total white blood cell count (WBC), absolute neutrophil count (ANC), absolute monocyte count (AMC), absolute lymphocyte count (ALC), relative percent of ANC, AMC and ALC to total WBC, and median absolute CD3 count were evaluated. There was no statistically significant difference between these median baseline pre-apheresis values in responders (CMR/PMR, N=108) compared to non-responders (PMD/SMD, N=51). Regarding safety outcomes, 11 patients (7%) had grade 0 cytokine release syndrome (CRS), 77(52%) grade 1 and 61(41%) grade ≥2 events. A total of 101 patients had documented highest grade immune mediated neurotoxicity (ICANS), with 64 patients (63%) grade 0, 23(23%) grade 1 and 14(14%) grade ≥2 events. Difference in median AMC percent of total WBC was a significant predictor of developing CRS, with Gr 0: 14.8%(12.2-600), Gr 1: 11.5%(0-37.5) vs Gr ≥2: 12.0%(1.4-35.7) (p=0.004). There was no other statistically significant difference between median baseline pre-apheresis values and highest grade CRS or ICANS. Conclusion : Our real-world analysis did not identify peripheral CD3, WBC, ANC, ALC or AMC as predictors of response to CD19 CAR-T cell therapy in LBCL. We found that in this population, higher AMC to WBC ratio was associated with more frequent occurrence of CRS. Further studies are required to ascertain practical predictors for response and toxicity with CAR-T cell therapy.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».