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Enregistrement W3213194096 · doi:10.1182/blood-2021-145883

Event-Free and Overall Survival in over 6,000 Patients Treated with Frontline Immunochemotherapy for Follicular Lymphoma between 2002-2018: First Report from the International FLIPI24 Consortium

2021· article· en· W3213194096 sur OpenAlexaff
Matthew J. Maurer, Vít Procházka, Christopher R. Flowers, Lasse Hjort Jakobsen, Diego Villa, Caroline E. Weibull, Elliot Cahn, Hervé Ghesquières, Robert Kridel, Maher K. Gandhi, Chan Y. Cheah, Eliza A. Hawkes, John F. Seymour, Ciara L. Freeman, Michael Roost Clausen, Björn E. Wahlin, Brian K. Link, Karin Ekstroem Smedby, Laurie H. Sehn, Marek Trněný, Tarec Christoffer El‐Galaly, James R. Cerhan

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensBC Cancer AgencyPrincess Margaret Cancer CentreSpinal Cord Injury BCUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésFollicular lymphomaMedicineEvent (particle physics)Internal medicineOncologyLymphoma

Résumé

récupéré en direct d'OpenAlex

Abstract Background: CD20 antibody plus alkylator and/or anthracycline based immunochemotherapy (IC) is a standard frontline therapy for patients with follicular lymphoma (FL) with 10-year event-free survival (EFS) and overall survival (OS) rates of approximately 50% and 80% respectively in long-term follow-up of clinical trials. Currently available clinical prognostic indices for FL have been designed using PFS and OS endpoints. Early events, commonly defined as progression of disease within 24 months (POD24) or early transformation to a more aggressive histology, are associated with inferior outcomes and increased risk of death due to refractory FL. Timely identification of the minority of patients with elevated mortality risk might enhance clinical management and research strategies. The FLIPI24 Consortium was created to develop a clinical prognostic index using early events as the primary endpoint. We report the outcomes for the pooled cohort and investigate the implications of therapy patterns on potential model development. Methods: Individual patient data were pooled and harmonized from 11 prospective observational cohorts from Europe, North America, and Australia. Patients who were diagnosed with grades 1-3A FL and initiated frontline IC were eligible. EFS was defined as time from start of IC to progression, relapse, retreatment (2nd line), histologic transformation, or death due to any cause. Early events were defined using status at 24 months from start of IC. OS was defined as time from start of IC to death due to any cause. Kaplan Meier curves and Cox proportional hazards models were used to evaluate outcomes by clinical features and therapy types. Results: 9006 patients were abstracted and harmonized, 6111 patients initiated frontline IC between 2002 and 2018 and were included in this analysis. Median age at diagnosis was 61 years (IQR 52-69) and 50% were male. Complete FLIPI data were available in 5637 patients (92%) and 46%, 32%, and 22% were low, intermediate, and high risk, respectively. IC type was 3079 R-CHOP or like (50%) , 1529 R-CVP or like (25%), 918 R-bendamustine (B-R) or like (15%), and 585 fludarabine or other alkylator based IC (10%); 3187 received CD20 antibody maintenance (52%). Patients receiving R-CHOP were younger, more frequently grade 3A, and more frequently had elevated LDH; differences in other characteristics by IC type were not clinically meaningful. At median follow-up of 42 months (IQR 17-72), 2647 patients (43%) had an event (any) and 1494 patients (25%) died. Median survival after an early (non-death) event was 49 months (95% CI: 41-58); 5-year OS was 46% (95% CI: 43-49) compared to 89% (95% CI: 88-90) in patients without POD24. Across all IC types, EFS estimates at 2 and 10 years from start of IC were 80% (95% CI:79-81) and 49% (95% CI:48-51) and OS estimates were 92% (95% CI: 91-92) and 70% (95% CI: 69-72), respectively. FLIPI was highly associated with both EFS (c-statistic=0.61) and OS (c-statistic=0.65) from the initiation of IC (both p<0.0001). There were significant differences in EFS and OS by IC type (both p<0.0001) and use of maintenance was associated with prolonged EFS in landmark analyses at both 6 and 12 months from initiation of IC (both p<0.0001). Treatment patterns changed significantly over the study timeframe. Use of B-R and/or maintenance increased to 30% and 70% respectively in N=2937 patients treated in 2010-2018 (Era2) compared to <1% and 40% respectively in N=3174 patients treated 2002-2009 (Era1). EFS was significantly higher for Era2 compared to Era1 (HR=0.77, 95% CI: 0.71-0.83), which remained significant after adjustment for FLIPI (EFS HR=0.82, 95% CI: 0.76-0.89). However, the association between treatment eras and overall survival was weaker (HR=0.89, 95% CI: 0.79-0.99) and not significant after adjusting for baseline FLIPI (OS HR=0.99, 95% CI: 0.88-1.10). Conclusion: EFS and OS from this large pooled analysis of observational cohorts is similar to long-term follow-up of randomized clinical trials in the IC era and support the use of these data for model development. Modeling efforts for early events should adjust for initial IC selection and use of maintenance therapy. Utilization of bendamustine and/or maintenance therapy increased over the study timeframe from 2002-2018, and Era2 was associated with improved EFS but not OS. This cohort provides comprehensive and robust observational data to define clinical predictors in IC treated patients. Figure 1 Figure 1. Disclosures Maurer: Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Flowers: Janssen: Research Funding; Takeda: Research Funding; National Cancer Institute: Research Funding; Biopharma: Consultancy; BeiGene: Consultancy; Amgen: Research Funding; Celgene: Consultancy, Research Funding; Xencor: Research Funding; Acerta: Research Funding; Bayer: Consultancy, Research Funding; Sanofi: Research Funding; 4D: Research Funding; Adaptimmune: Research Funding; Allogene: Research Funding; EMD: Research Funding; TG Therapeutics: Research Funding; Burroughs Wellcome Fund: Research Funding; Kite: Research Funding; AbbVie: Consultancy, Research Funding; Cellectis: Research Funding; Denovo: Consultancy; Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding; Karyopharm: Consultancy; Gilead: Consultancy, Research Funding; Genmab: Consultancy; Epizyme, Inc.: Consultancy; Novartis: Research Funding; Nektar: Research Funding; Morphosys: Research Funding; Iovance: Research Funding; Spectrum: Consultancy; Pfizer: Research Funding; Ziopharm: Research Funding; Guardant: Research Funding; Eastern Cooperative Oncology Group: Research Funding; SeaGen: Consultancy; Pharmacyclics/Janssen: Consultancy; Genentech/Roche: Consultancy, Research Funding; Pharmacyclics: Research Funding. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. Weibull: Jansen-Cilag: Other: part of a research collaboration between Karolinska Institutet and Janssen Pharmaceutica NV for which Karolinska Institutet has received grant support. Ghesquieres: Janssen: Honoraria; Mundipharma: Consultancy, Honoraria; Roche: Consultancy; Celgene: Consultancy, Honoraria; Gilead Science: Consultancy, Honoraria. Kridel: Gilead Sciences: Research Funding. Gandhi: Janssen: Research Funding; Novartis: Honoraria. Cheah: Celgene: Research Funding; TG Therapeutics: Consultancy, Honoraria, Other: advisory; Loxo/Lilly: Consultancy, Honoraria, Other: advisory; AstraZeneca: Consultancy, Honoraria, Other: advisory; AbbVie: Research Funding; Beigene: Consultancy, Honoraria, Other: advisory; Ascentage pharma: Consultancy, Honoraria, Other: advisory; Gilead: Consultancy, Honoraria, Other: advisory; MSD: Consultancy, Honoraria, Other: advisory, Research Funding; Janssen: Consultancy, Honoraria, Other: advisory; Roche: Consultancy, Honoraria, Other: advisory and travel expenses, Research Funding. Hawkes: Gilead: Membership on an entity's Board of Directors or advisory committees; Merck Sharpe Dohme: Membership on an entity's Board of Directors or advisory committees; Antigene: Membership on an entity's Board of Directors or advisory committees; Regeneron: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squib/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck KgA: Research Funding; Specialised Therapeutics: Consultancy; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel and accommodation expenses, Research Funding, Speakers Bureau; Janssen: Speakers Bureau. Seymour: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sunesis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Mei Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Morphosys: Honoraria, Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau. Freeman: Amgen: Honoraria; Celgene: Honoraria; Sanofi: Honoraria, Speakers Bureau; Incyte: Honoraria; Abbvie: Honoraria; Teva: Research Funding; Roche: Research Funding; Janssen: Honoraria, Speakers Bureau; Seattle Genetics: Honoraria; Bristol Myers Squibb: Honoraria, Speakers Bureau. Clausen: Abbvie: Honoraria, Mem

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,011
Tête enseignante GPT0,237
Écart entre enseignants0,226 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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