234 | POST HOC ANALYSIS OF OUTCOMES BY POD24 STATUS FROM THE inMIND STUDY OF TAFASITAMAB PLUS LENALIDOMIDE AND RITUXIMAB IN RELAPSED OR REFRACTORY FOLLICULAR LYMPHOMA
Notice bibliographique
Résumé
Introduction: Patients with follicular lymphoma (FL) commonly experience relapse; prognosis is worse in patients with disease progression within 24 months (POD24). inMIND (NCT04680052), a phase 3, double-blind, randomised, placebo (pbo)-controlled, multicentre international trial reported a significant, clinically meaningful 57% reduction in risk of progression, relapse or death with tafasitamab (tafa) added to lenalidomide (len) plus rituximab (R) (tafa+len+R) compared with addition of pbo to len plus R (pbo+len+R) in patients with relapsed or refractory (R/R) FL (Sehn LH, et al. Blood. 2024;144(Suppl. 2):LBA1). PFS benefit was observed regardless of POD24 status, defined as disease progression within 24 months of initial FL diagnosis. This post hoc analysis reports PFS and other outcomes with POD24 defined as disease progression within 24 months of start of initial treatment, to assess whether the positive outcomes observed with tafa+len+R compared to pbo+len+R were maintained regardless of the definition of POD24. Additionally, PFS in patients with progression of disease within 12 months of start of initial treatment (POD12) was assessed. Methods: Patients ≥ 18 y with R/R CD19+ and CD20+ FL (grade 1–3A), ECOG PS ≤ 2, requiring treatment after ≥ 1 prior systemic therapy including an anti-CD20 monoclonal antibody (mAb), were randomised 1:1 to receive tafa+len+R or pbo+len+R for 12 cycles. Endpoints evaluated included investigator-assessed PFS, PET-CR, ORR, and TTNT. Results: As defined from start of initial treatment: 249 patients (45.4%) were POD24 positive, 282 (51.5%) were POD24 negative, and 17 (3.1%) had unknown status. Overall, patient characteristics were similar across treatment arms (not shown) and POD24-positive versus POD24-negative groups (median age, 63.0 vs. 66.0 y; GELF criteria met, 82.7% vs. 83.0%; median prior lines of therapy, 1.0 in each group). However, more POD24-positive patients had negative prognostic factors: high-risk FLIPI (57.4% vs. 46.8%); refractory to prior anti-CD20 mAb (66.7% vs. 20.2%). Investigator-assessed PFS was significantly longer with tafa+len+R among POD24-positive and POD24-negative patients (hazard ratio [95% CI], 0.4 [0.3, 0.7] and 0.5 [0.3, 0.7]). Tafa+len+R also improved PET-CR, ORR and TTNT (Table). Addition of tafa to len+R improved PFS by investigator regardless of POD12 status compared to pbo (Table). Conclusions: POD24 is a known predictor of early mortality in FL. In inMIND, tafa+len+R reduced the risk of progression, relapse or death in patients with R/R FL regardless of POD24 status and the definition of POD24 used. Benefit of adding tafa was also observed regardless of POD12 status, and in other outcomes including PET-CR, ORR and TTNT. Thus, tafa+len+R represents a potential new treatment option for these patients with R/R FL regardless of their disease progression status. Research funding declaration: Incyte Corporation, Wilmington, DE Encore Abstract: ASCO 2025; EHA 2025 Keywords: combination therapies; immunotherapy; indolent non-Hodgkin lymphoma Potential sources of conflict of interest: L. H. Sehn Consultant or advisory role: AbbVie, Acerta, Apobiologix, AstraZeneca, Celgene, Debiopharm, Genentech, Genmab, Gilead Sciences, Incyte Corporation, Janssen, Karyopharm Therapeutics, Kite Pharma, Lundbeck, Merck, MorphoSys, Novartis, Sandoz, Takeda, TG Therapeutics, Verastem Oncology, Teva, Roche, Seattle Genetics Other remuneration: Teva, Roche, Seattle Genetics K. Hübel Consultant or advisory role: AbbVie, Beigene, Bristol Myers Squibb, EUSA/Recordati, Gilead Sciences, Incyte Corporation, Novartis, Roche, Servier Other remuneration: AbbVie, Beigene, Bristol Myers Squibb, EUSA/Recordati, Gilead Sciences, Incyte Corporation, Novartis, Roche, Servier S. Luminari Consultant or advisory role: AbbVie, Bristol Myers Squibb, Genmab, Incyte Corporation, Janssen, Kite, Novartis, Regeneron, Roche C. W. Scholz Consultant or advisory role: Bristol Myers Squibb, Celgene, Daiichi Sankyo, Gilead Sciences, Hexal, Incyte Corporation, Janssen, Merck Serono, Novartis, Roche, Takeda Honoraria: AstraZeneca, Gilead Sciences, Janssen, Pfizer, Roche A. Salar Consultant or advisory role: AbbVie, AstraZeneca, Beigene, Incyte Corporation, Ipsen, Roche, Sandoz Other remuneration: AbbVie, AstraZeneca, Beigene, Incyte Corporation, Ipsen, Roche, Sandoz, Gilead Sciences S. Paneesha Honoraria: AbbVie, Beigene, Celgene, Gilead Sciences, Janssen, Roche B. E. Wahlin Consultant or advisory role: Roche Honoraria: Incyte Corporation, MorphoSys Other remuneration: Gilead Sciences H. Lee Consultant or advisory role: AstraZeneca, BeiGene, Gilead Sciences Honoraria: Roche A. Jiménez-Ubieto Consultant or advisory role: AbbVie, AstraZeneca, Genmab, Kite, Lilly Other remuneration: AbbVie, Incyte Corporation, Janssen, Kite, Novartis, Roche J. Sancho Consultant or advisory role: AbbVie, AstraZeneca, Beigene, Bristol Myers Squibb-Celgene, Gilead-Kite, Incyte Corporation, Janssen, Lilly, Myltenyi Biomedicine, Novartis, Roche, Sobi Honoraria: AbbVie, Beigene, Bristol Myers Squibb-Celgene, Gilead-Kite, Incyte Corporation, Janssen, Lilly, Roche T. M. Kim Consultant or advisory role: Amgen, AstraZeneca/MedImmune, Boryung, Daiichi-Sankyo, HK inno.N, IMBDx. Inc., Janssen, Novartis, Regeneron, Roche/Genentech, Samsung Bioepis, Takeda, Yuhan E. Domingo Domenech Consultant or advisory role: BeiGene, Bristol Myers Squibb-Celgene, Ideogen, Takeda Other remuneration: BeiGene, Bristol Myers Squibb-Celgene, Ideogen, Takeda T. Kumode Honoraria: Janssen, Ono Pharmaceutical C. Poh Consultant or advisory role: Acrotech, AstraZeneca, Ipsen, Seagen Other remuneration: Astex, Dren Bio, Incyte Corporation, Seagen C. Thieblemont Consultant or advisory role: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Incyte Corporation, Janssen, Kite, Novartis, Roche, Takeda Honoraria: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Incyte Corporation, Janssen, Kite, Novartis, Roche, Takeda Educational grants: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Janssen, Kite, Novartis, Roche, Takeda Other remuneration: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Incyte Corporation, Janssen, Kite, Novartis, Roche, Takeda, Janssen, Roche D. Deeren Consultant or advisory role: Alexion, Bristol Myers Squibb, Incyte Corporation, Novartis, Sanofi, Sobi, Takeda Other remuneration: Alexion, Amgen, Novartis, Roche, and Sobi E. de Wit Employment or leadership position: Incyte Stock ownership: Incyte M. Arbushites Employment or leadership position: Incyte Stock ownership: Incyte O. Bortolami Employment or leadership position: Incyte Stock ownership: Incyte M. Trneny Consultant or advisory role: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Gilead Sciences, Incyte Corporation, Janssen, MorphoSys, Roche, Takeda Honoraria: AbbVie, Amgen, Bristol Myers Squibb, Gilead Sciences, Incyte Corporation, Janssen, MorphoSys, Roche, Takeda Educational grants: AbbVie, Bristol Myers Squibb, Gilead Sciences, Janssen, Roche, Takeda
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 | 0,000 | 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 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 ».