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Enregistrement W4405047886 · doi:10.1182/blood-2024-194382

Treatment with First-Line Ibrutinib Improves Overall Survival in Patients with Chronic Lymphocytic Leukemia (CLL) and High-Risk Genomic Features to Rates Approximating an Age-Matched US Population: Pooled Analysis of Phase 3 Trials with 10 Years of Follow-up

2024· article· en· W4405047886 sur OpenAlexaff
Jan A. Burger, Neil E. Kay, John N. Allan, Paul M. Barr, Jacqueline C. Barrientos, Carolyn Owen, Victoria Wang, Hsin-Hui Huang, Lynne Neumayr, Christopher Abbazio, Gabriel Krigsfeld, Paolo Ghia, Tait D. Shanafelt

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Lymphocytic Leukemia Research
Établissements canadiensUniversity of Calgary
Organismes subventionnairesModernaJuno TherapeuticsIncyteBeiGenePharmacyclicsGenentechMEI PharmaTG TherapeuticsBristol-Myers SquibbEli Lilly and CompanyAstraZenecaMorphoSysCelgeneSeagenGilead Sciences
Mots-clésIbrutinibChronic lymphocytic leukemiaInternal medicineMedicineOncologyPopulationSurvival analysisLeukemiaImmunology

Résumé

récupéré en direct d'OpenAlex

Introduction: Ibrutinib, a Bruton tyrosine kinase inhibitor (BTKi), changed the treatment landscape by demonstrating improved overall survival (OS) compared with chemotherapy/chemoimmunotherapy across multiple phase 3 trials in patients (pts) with CLL, including those with high-risk genomic features. Recently, data were reported for pts treated with ibrutinib in the phase 3 RESONATE-2 trial with up to 10 years of follow-up, representing the longest follow-up of any BTKi used in first-line treatment of CLL. With the most robust long-term follow-up data among BTKis, ibrutinib therapy trials are uniquely positioned to assess the long-term OS benefit of first-line BTKi treatment in pts with CLL across pt subgroups. We previously demonstrated that first-line ibrutinib is associated with OS rates that are similar to those in the age-matched general population, with a median follow-up of 5.9 years since initial diagnosis (Ghia P et al. HemaSphere 2024), but it remains unclear whether this holds true for pts with high-risk genomic features. This updated analysis evaluated long-term OS outcomes with a median follow-up of 8 years since randomization and 10 years since initial diagnosis in a pooled population of pts with previously untreated CLL, including those with high-risk features, who received first-line ibrutinib treatment in 2 phase 3 trials with comparison of survival estimates to the US age-matched general population. Methods: Data were pooled for pts who received first-line treatment with single-agent ibrutinib or ibrutinib + rituximab in the RESONATE-2 (NCT01722487) and ECOG-ACRIN E1912 (NCT02048813) trials, respectively. OS probabilities from the time of randomization and from the time of initial diagnosis for ibrutinib-treated pts were compared with an age-matched general population using 2021 life tables for the total US population published by the Centers for Disease Control and Prevention using the Kaplan-Meier method. Subgroup analyses were performed for high-risk pts, defined as those with del(11q), del(17p), mutated TP53, and/or unmutated IGHV (uIGHV). Results: A total of490 pts were pooled across the 2 studies: 352 pts (71.8%) were treated with ibrutinib + rituximab, and 135 pts (27.6%) were treated with single-agent ibrutinib; 3 pts did not receive study treatment. The median age at time of randomization was 61 years; 36.5% (179/490) were aged ≥65 years, 21.8% had del(11q), 7.8% had del(17p) and/or mutated TP53, and 54.7% had uIGHV. The median time from initial CLL diagnosis to randomization was 20.9 months (range, 0.0-341.8); the median follow-up was 123.5 months (10.3 years) from initial diagnosis and 99.2 months (8.3 years) from the time of randomization. From the time of randomization, estimated 9-year OS rates were 81.2% (95% CI, 76.8-84.9) in all ibrutinib-treated pts versus 82.0% (95% CI, 78.3-85.2) in the age-matched population (hazard ratio [HR] 1.17; 95% CI, 0.86-1.58). In high-risk pts, estimated 9-year OS rates were 79.5% (95% CI, 73.5-84.3) for ibrutinib-treated pts versus 83.2% (95% CI, 78.5-86.9) in the age-matched general population (HR 1.24; 95% CI, 0.84-1.84). In pts aged ≥65 years, estimated 9-year OS rates were 68.7% (95% CI, 60.5-75.6) for ibrutinib-treated pts and 68.7% (95% CI, 61.4-75.0) in the age-matched general population (HR 1.12; 95% CI, 0.77-1.63). In pts aged <65 years, estimated 9-year OS rates were 89.3% (95% CI, 84.6-92.7) for ibrutinib-treated pts and 90.0% (95% CI, 86.1-92.9) in the age-matched general population (HR 1.15; 95% CI, 0.68-1.94). From the time of initial diagnosis, estimated 15-year OS rates were 78.4% (95% CI, 72.8-83.0) in all ibrutinib-treated pts versus 72.0% (95% CI, 67.8-75.7) in the age-matched general population (HR 0.83; 95% CI, 0.62-1.11). Study treatment had been discontinued in 59.8% (293/490) of pooled ibrutinib-treated pts; the most frequent reasons for discontinuation were adverse events (43.0%; 126/293) and progressive disease (20.5%; 60/293). Study treatment was ongoing in 31.8% of pooled pts (156/490). Conclusions: With the longest follow-up time for any commercially available targeted therapy, this pooled analysis demonstrates that, regardless of evaluation from randomization or initial diagnosis, and irrespective of age or high-risk features, first-line treatment with ibrutinib provides long-term OS benefit with survival estimates that appear similar to those of a US age-matched cohort.

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)0,007
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: Méta-analyse
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,039

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0030,010
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
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 Opus0,018
Tête enseignante GPT0,300
Écart entre enseignants0,283 · 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'étudeMéta-analyse
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
Publié2024
Routes d'admission1
Résumé présentoui

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