IMPROVED OUTCOMES IN PATIENTS (PTS) WITH BCL2‐POSITIVE DIFFUSE LARGE B‐CELL LYMPHOMA (DLBCL) TREATED WITH VENETOCLAX (VEN) PLUS R‐CHOP: RESULTS FROM THE PHASE 2 CAVALLI STUDY
Notice bibliographique
Résumé
Introduction: BCL2 and BCL2 plus MYC overexpression, and coexisting BCL2 and MYC translocation (double-hit [DH]) are associated with poor outcomes in DLBCL. Ven, a highly selective BCL2 inhibitor, may enhance the current standard regimen of rituximab (R)+CHOP chemotherapy. Phase (Ph) 1b of CAVALLI (NCT02055820) established Ven 800 mg on Days (D) 1−4, Cycle (C) 1 and D1−10, C2−8 as the recommended Ph 2 dose combined with R-CHOP in first-line (1L) DLBCL. We report safety, efficacy and biomarker analyses of CAVALLI Ph2 (data cut-off, July 13 2018). Methods: Eligible pts were ≥18 yrs old with 1L DLBCL, ECOG performance status ≤2 and IPI score 2–5. Oral Ven 800 mg was given on D1–4, C1 and D1−10, C2−8 combined with R (8 Cs) and CHOP (6−8 Cs); 21-day Cs. Primary endpoint was PET-complete response (CR) at end of treatment (EOT; modified Lugano criteria 2014). Secondary endpoints were PFS, OS and safety. The R-CHOP control arm of GOYA (564 pts, IPI 2–5) was used as a historical control. Factors affecting completion of 8 treatment Cs were assessed using multivariate analysis (MVA). Time-to-event endpoints were compared using adjusted Cox regression. Biomarker analyses included BCL2 and MYC immunohistochemistry (IHC), BCL2 and MYC translocations by fluorescence in situ hybridization (FISH) and cell of origin (COO) by NanoString. Results: Of 211 pts enrolled in CAVALLI, 208 received any treatment and were analyzed for efficacy and safety. Baseline characteristics for CAVALLI vs GOYA were similar, but more Ann Arbor Stage IV (65% vs 47%) and BCL2 IHC+ (58% vs 49%) pts enrolled in CAVALLI. In the overall population, EOT PET-CR rates were similar (CAVALLI, 69%; GOYA, 63%), while PET-CR rates were higher in CAVALLI for BCL2 FISH+ and DH pts (Table). PFS was improved in the overall and BCL2 IHC+ populations vs GOYA (Figure); PFS benefit in BCL2 IHC+ pts was observed across ABC and GCB COO subtypes. There was also evidence of OS benefit vs GOYA; HR 0.7, 95% CI 0.43–1.1 (overall), HR 0.7, 95% CI 0.35–1.2 (BCL2 IHC+). Grade 3–4 AEs occurred in 86% of pts in CAVALLI vs 66% in GOYA, mainly cytopenia, febrile neutropenia (FN) and infection. A trend towards lower neutropenia and FN/infection incidence was seen in pts receiving G-CSF prophylaxis. On MVA, age <60 yrs was the only factor to predict completion of 8 treatment Cs (p=0.002). There were 4 fatal AEs (2%) in CAVALLI vs 30 (5%) in GOYA, but follow-up was longer in GOYA (29.6 vs 22.3 months). The high AE rate in CAVALLI led to dose interruptions/discontinuations; 61% of pts received >90% relative dose intensity (RDI) of Ven; 73% received >90% RDI for cyclophosphamide and doxorubicin. The RDI of chemotherapy was similar in GOYA. Acknowledgments: Venetoclax is being developed in collaboration between Genentech and AbbVie. Genentech and AbbVie provided financial support for the study. Third-party editorial assistance was provided, funded by F. Hoffmann-La Roche Ltd. This abstract has been previously submitted to EHA 2019. Keywords: BCL2; diffuse large B-cell lymphoma (DLBCL); venetoclax. Disclosures: Morschhauser, F: Consultant Advisory Role: Gilead; Honoraria: Celgene, Roche, Janssen, Bristol-Myers Squibb, Servier, Epizyme. Flinn, I: Consultant Advisory Role: Abbvie, Seattle Genetics, TG Therapeutics, Verastem; Research Funding: Acerta, Agios, Calithera Biosciences, Celgene, Constellation Pharmaceuticals, Genentech, Gilead Sciences, Incyte, Infinity Pharmaceuticals, Janssen, Karyopharm Therapeutics, Kite Pharma, Novartis, Pharmacyclics, Portola Pharmaceuticals, Roche, Seattle Genetics, TG Therapeutics, Trillim Therapeutics, Abbvie, ArQule, BeiGene, Curis, FoRMA Therapeutics, Forty Seven, Merck, Pfizer, Takeda, Teva, Verastem. Gasiorowski, R: Honoraria: Novartis, MSD, Takeda, Abbvie. Illés, Á: Consultant Advisory Role: Janssen, Celgene, Novartis, Pfizer, Takeda, Roche; Honoraria: Janssen, Celgene, Novartis, Pfizer, Takeda, Roche; Research Funding: Takeda, Seattle Genetics; Other Remuneration: Expenses: Novartis, Janssen, Pfizer, Roche. Feugier, P: Consultant Advisory Role: Roche, Janssen, Gilead, Abbvie, Amgen; Honoraria: Roche, Janssen, Gilead, Abbvie, Amgen; Other Remuneration: Expenses: Roche, Janssen, Gilead, Abbvie, Amgen. Greil, R: Consultant Advisory Role: Celgene, Novartis, Roche, Bristol-Myers Squibb, Takeda, Abbvie, AstraZeneca, Janssen, MSD, Merck, Gilead; Honoraria: Celgene, Roche, Merck, Takeda, Sandoz, AstraZeneca, Novartis, Amgen, Bristol-Myers Squibb, MSD, Abbvie, Gilead; Research Funding: Celgene, Roche, Merck, Takeda, AstraZeneca, Novartis, Amgen, Bristol-Myers Squibb, MSD, Sandoz; Other Remuneration: Expenses: Roche, Amgen, Janssen, AstraZeneca, Novartis, MSD, Celgene, Gilead. Johnson, N: Consultant Advisory Role: Roche; Honoraria: Roche. Larouche, J: Consultant Advisory Role: AstraZeneca; Research Funding: AstraZeneca, Roche, Merck, BMS, Takeda; Other Remuneration: Expenses: AstraZeneca. Lugtenburg, P: Consultant Advisory Role: Roche, Takeda, Servier, Bristol-Myers Squibb, Celgene, Sandoz, Genmab; Research Funding: Roche, Servier, Takeda. Salles, G: Consultant Advisory Role: Roche/Genentech, Gilead, Janssen, Celgene, Novartis, Merck, Pfizer, Acerta Pharma, Kite Pharma, Servier, MorphoSys, Epizyme; Honoraria: Roche/Genentech, Amgen, Janssen, Celgene, Servier, Gilead, Novartis, Abbvie, Merck, Takeda, MorphoSys. Trněný, M: Consultant Advisory Role: Takeda, Bristol-Myers, Squibb, Incyte, Abbvie, Amgen, Roche, Gilead Sciences, Janssen, Celgene, MorphoSys; Honoraria: Janssen, Gilead Sciences, Takeda, Bristol-Myers Squibb, Amgen, Abbvie, Roche, MorphoSys, Incyte; Research Funding: Roche; Other Remuneration: Expenses: Gilead Sciences, Takeda, Bristol-Myers Squibb, Roche, Janssen, Abbvie. de Vos, S: Consultant Advisory Role: Bayer, Verastem. Mir, F: Employment Leadership Position: Roche. Kornacker, M: Employment Leadership Position: F. Hoffmann-La Roche Ltd.; Stock Ownership: F. Hoffmann-La Roche Ltd., Bayer AG, J&J. Punnoose, E: Employment Leadership Position: Genentech, Member of the Roche Group; Stock Ownership: Genentech, Member of the Roche Group; Other Remuneration: Patents, Royalties, other intellectual property: Genentech, Member of the Roche Group. Samineni, D: Employment Leadership Position: Genentech; Stock Ownership: Roche. Szafer-Glusman, E: Employment Leadership Position: Genentech; Stock Ownership: Roche. Petrich, A: Employment Leadership Position: Abbvie; Stock Ownership: Abbvie; Other Remuneration: Expenses: Abbvie. Sinha, A: Employment Leadership Position: Roche; Stock Ownership: Roche. Spielewoy, N: Employment Leadership Position: Roche; Stock Ownership: Roche. Humphrey, K: Employment Leadership Position: Roche; Stock Ownership: Roche. Bazeos, A: Employment Leadership Position: Roche; Stock Ownership: Roche. Zelenetz, A: Consultant Advisory Role: Genentech/Roche, Gilead, Celgene, Janssen, Amgen, Novartis, Adaptive Biotech, MorphoSys, Gilead, Abbvie, AstraZeneca; Honoraria: Genentech/Roche, Gilead, Celgene, Janssen, Amgen, Novartis, Adaptive Biotech, MorphoSys, Gilead, Abbvie, AstraZeneca; Research Funding: MEI Pharma, Roche, Gilead, Beigene; Other Remuneration: Expenses: Genentech/Roche, Gilead, Celgene, Janssen, Amgen, Novartis, Adaptive Biotech, MorphoSys, Gilead, Abbvie, AstraZeneca; DMC chair: Beigene.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 |
| 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 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 ».