76 | GLOFITAMAB PLUS GEMCITABINE AND OXALIPLATIN (Glofit‐GemOx) IN PATIENTS WITH RELAPSED/REFRACTORY (R/R) DIFFUSE LARGE B‐CELL LYMPHOMA (DLBCL): 2‐YEAR FOLLOW‐UP OF STARGLO
Notice bibliographique
Résumé
Introduction: Glofitamab, a CD20:CD3 bispecific antibody, has shown durable responses as fixed duration monotherapy in R/R DLBCL after ≥ 2 prior lines of therapy (LOT; Dickinson et al. NEJM 2022). In the Phase 3 STARGLO trial, Glofit-GemOx demonstrated overall survival (OS) and progression-free survival (PFS) benefits over rituximab (R)-GemOx in autologous stem cell transplant (ASCT)-ineligible R/R DLBCL (Abramson et al. Lancet 2024). Here, we present updated efficacy and safety from the STARGLO trial (NCT04408638), including landmark analyses of patients (pts) in complete remission (CR). Methods: Pts were randomized 2:1 to receive Glofit-GemOx (8 cycles plus 4 cycles glofitamab monotherapy) or R-GemOx (8 cycles) and stratified by number of prior LOT (1 vs. ≥ 2) and refractoriness to their last therapy. After obinutuzumab pretreatment, glofitamab was given in Cycle (C) 1 as weekly step-up doses (2.5/10 mg) then 30 mg target dose every 21 days from C2 Day 1. Pts with only 1 prior LOT must have been ASCT-ineligible. Primary endpoint was OS. Secondary endpoints included independent review committee (IRC)-assessed PFS and CR rate. A landmark analysis of pts in CR at end of treatment (EOT) was performed. Results: Of 274 pts (Glofit-GemOx, n = 183; R-GemOx, n = 91), 172 (62.8%) had 1 prior LOT, 102 (37.2%) had ≥ 2 prior LOT, 153 (55.8%) were primary refractory, and 166 (60.6%) were refractory to their last therapy. Baseline characteristics were unchanged compared with the primary analysis and well balanced across arms. With 2 years (yrs) of follow-up (data cut off: June 17, 2024; median follow-up: 24.7 months [mo]), Glofit-GemOx continued to confer superior OS (median: not evaluable [NE] vs. 13.5 mo; hazard ratio [HR] 0.60, 95% confidence interval [CI]: 0.42–0.85), median IRC-assessed PFS (13.8 vs. 3.6 mo; HR 0.41, 95% CI: 0.29–0.58), and CR rate (58.5 vs. 25.3%) versus R-GemOx. For Glofit-GemOx-treated pts in CR (n = 107), median duration of CR was not reached (95% CI: 27.2–NE; median CR follow-up, 18.2 mo [range: 15.2–19.3]). In pts with a CR at EOT (n = 82), the OS and PFS rates 1 yr after EOT were 89.3% and 82.4%, respectively. The Glofit-GemOx safety profile was unchanged. Cytokine release syndrome (CRS) was the most common adverse event in glofitamab-exposed pts (Grade [Gr] 1, 32.0%; Gr 2, 10.5%; Gr 3, 2.3%). Events consistent with immune effector cell-associated neurotoxicity syndrome occurred in 4 pts (all concurrent with CRS; most Gr 1–2 [n = 3]). Exploratory biomarker and immune recovery data will be presented. Conclusions: With 2 yrs of follow-up, Glofit-GemOx sustained a clinically meaningful benefit in OS and PFS versus R-GemOx in ASCT-ineligible pts with R/R DLBCL, with most (82%) pts in CR at EOT still in remission. The safety profile was consistent with known risks of each drug. The updated analyses demonstrate durable remissions and maintained OS benefit in pts with R/R DLBCL treated with fixed duration Glofit-GemOx. Research funding declaration: STARGLO (GO41944) is sponsored by F. Hoffmann-La Roche Ltd. Third-party editorial assistance, under the direction of all authors, was provided by Roisin Weaver, MSc, of Ashfield MedComms, an Inizio company, and was funded by F. Hoffmann-La Roche Ltd. Encore Abstract: © 2025 American Society of Clinical Oncology, Inc. Reused with permission. This abstract was accepted and previously presented at the ASCO 2025 Annual Meeting. All rights reserved. Keywords: aggressive B-cell non-Hodgkin lymphoma; immunotherapy Potential sources of conflict of interest: J. S. Abramson Consultant or advisory role: Celgene, Novartis, Abbvie, Kite (a Gilead company), EMD Serono, MorphoSys, Alimera Sciences, Karyopharm Therapeutics, Bristol-Myers Squibb, C4 Therapeutics, BeiGene, AstraZeneca, Incyte, Bluebird Bio, Kymera, Epizyme, Genmab, MustangBio, Ono Pharmaceutical, Century Therapeutics, Lilly, Caribou Biosciences, Janssen, Takeda, Interius Biotherapeutics, Cellectar, Seagen, Roche/Genentech, ADC Therapeutics, Foresight Diagnostics. Honoraria: Regeneron, AstraZeneca, Janssen, Bristol-Myers Squibb/Celgene, Abbvie, Kite (a Gilead company). Other remuneration: Research funding: Seagen, Bristol-Myers Squibb/Celgene, Cellectis, MustangBio, Regeneron, Merck. M. Ku Consultant or advisory role: Roche, AbbVie. Other remuneration: Research funding: Roche, BeiGene. M. Hertzberg Consultant or advisory role: Roche, Gildead. Honoraria: Pfizer, Takeda, Janssen. C. P. Fox Consultant or advisory role: AbbVie, Arvinas, BMS, GenMab, Gilead/Kite, Incyte, Morphosys, Ono, Roche, SERB, SOBI. Honoraria: AbbVie, Gilead/Kite, Incyte, Roche, SERB. Other remuneration: Speaker's bureau: AbbVie, Roche, Kite/Gilead. Research funding: AbbVie, BeiGene, Genmab, Incyte, Roche. C. Herbaux Consultant or advisory role: Roche, Janssen, Abbvie, Gilead/Kite, Incyte, Novartis. Honoraria: Roche, Janssen, Abbvie, Gilead/Kite, Incyte, Novartis. Educational grants: Roche, Janssen, Abbvie, Gilead/Kite, Incyte, Novartis. Other remuneration: Research funding: AbbVie, Takeda. D. H. Yoon Consultant or advisory role: Roche, Janssen, Amgen, Celgene, Novartis, ABclonal, GI cell, Pharos iBio. Honoraria: Roche, Janssen, Celgene, Kirin Pharmaceuticals, Takeda. Other remuneration: Research funding (self): Samyung, Roche/Genentech, Janssen Oncology, Boryung. Research funding (institution): Celltrion. W. S. Kim Other remuneration: Research funding: Sanofi, Beigene, Boryong, Roche, Kyowa-Kirin, Donga. H. Abdulhaq Consultant or advisory role: Novartis, BMS, Genentech, Inc., AbbVie, ADC therapeutics, Pfizer. Honoraria: Novartis, BMS, Genentech, Inc., AbbVie, ADC therapeutics, Pfizer. Educational grants: AbbVie, Genentech, Inc., Actrotech, AstraZeneca. Other remuneration: Speaker's bureau: Genentech, Inc., Alexion. Research funding: Novartis, BMS, Acrotech, ADC therapeutics, Genentech, Inc., Pfizer. W. Townsend Consultant or advisory role: Roche, Abbvie, Kite, Sobi. Honoraria: Roche, Abbvie, Kite, Sobi. Educational grants: Roche, AbbVie. Other remuneration: Research funding (institution): University College London (UCL). My institution (UCL) has received research funding from Roche for conduct of a clinical trial. E. Mulvihill Employment or leadership position: F. Hoffmann-La Roche Ltd. Stock ownership: F. Hoffmann-La Roche Ltd. Educational grants: F. Hoffmann-La Roche Ltd. V. Orellana-Noia Employment or leadership position: Genentech, Inc. Stock ownership: Genentech, Inc. (Roche). R. Ta Employment or leadership position: Genentech, Inc. Stock ownership: F. Hoffmann-La Roche. Educational grants: Genentech, Inc. Other remuneration: Research funding: Genentech, Inc. (salaried employee). H. Huang Employment or leadership position: F. Hoffmann-La Roche Ltd. Other remuneration: Patents, royalties, other intellectual property: F. Hoffmann-La Roche Ltd. M. J. Kallemeijn Employment or leadership position: F. Hoffmann-La Roche Ltd. A. Belousov Employment or leadership position: F. Hoffmann-La Roche Ltd. Stock ownership: F. Hoffmann-La Roche Ltd. Educational grants: F. Hoffmann-La Roche Ltd. A. Bottos Employment or leadership position: F. Hoffmann-La Roche Ltd. Stock ownership: F. Hoffmann-La Roche Ltd. L. Lundberg Employment or leadership position: F. Hoffmann-La Roche Ltd. Stock ownership: F. Hoffmann-La Roche Ltd. Other remuneration: Patents, royalties, other intellectual property: F. Hoffmann-La Roche Ltd. G. P. Gregory Consultant or advisory role: Roche/Genentech, BMS, Gilead/Kite, Prelude Therapeutics, Clinigen, Merck. Educational grants: Novartis. Other remuneration: Speaker's bureau: Roche/Genentech. Research funding: BeiGene, Merck.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».