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Enregistrement W4417014766 · doi:10.1182/blood-2025-3898

Impact of prognostic mutations on outcomes with fixed-duration acalabrutinib-venetoclax combinations versus chemoimmunotherapy: An exploratory analysis from AMPLIFY

2025· article· en· W4417014766 sur OpenAlexaff
Paolo Ghia, Barbara Eichhorst, Tomasz Wróbel, İnci Alacacıoğlu, Ana Rita Da Fonseca, Dennis Carney, Guillaume Cartron, Alina S. Gerrie, Don A. Stevens, Marianne de Borja, Toshifumi Fujimori, Ellie John, L. Alex Liggett, Gary De Jesus, Veerendra Munugalavadla, Jennifer Brown

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Lymphocytic Leukemia Research
Établissements canadiensSpinal Cord Injury BCUniversity of British ColumbiaAmorfix (Canada)University of British Columbia Hospital
Organismes subventionnairesnon disponible
Mots-clésChemoimmunotherapyObinutuzumabFludarabineIGHV@BendamustineRituximabChronic lymphocytic leukemiaExploratory analysisCyclophosphamide

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: The AMPLIFY trial evaluated fixed-duration acalabrutinib + venetoclax ± obinutuzumab (AV/AVO) vs chemoimmunotherapy (CIT) in fit patients (pts) with treatment-naive (TN) chronic lymphocytic leukemia (CLL) (Brown et al. NEJM 2025;392:748-62). In the ITT population, AV/AVO demonstrated prolonged progression-free survival (PFS) vs CIT. However, shorter PFS occurs with certain genetic factors, such as unmutated IGHV (uIGHV) and NOTCH1, even with targeted treatment (tx) (Tausch et al. Blood 2022;140(Suppl 1):839-41). This exploratory analysis evaluated the relationship between prognostic genetic aberrations and clinical outcomes in AMPLIFY. Methods AMPLIFY (ACE-CL-311; NCT03836261) is an ongoing, randomized, open-label, phase 3 trial in pts with TN CLL aged ≥18 y with ECOG performance status ≤2 and without del(17p) or TP53 mutation. Pts were randomized to receive AV (acalabrutinib, cycles [C] 1–14; venetoclax, C3–14), AVO (AV as described; obinutuzumab, C2−7), or investigator's choice of fludarabine + cyclophosphamide + rituximab or bendamustine + rituximab (FCR/BR, C1−6). Subgroup analyses were performed for blinded independent central review–assessed PFS and time to next tx (TTNT) according to baseline and disease characteristics for AV and AVO vs FCR/BR. Blood samples collected at baseline were analyzed centrally for genetic factors, including uIGHV and 6 mutations (ATM, CARD11, NOTCH1, BIRC3, MYD88, SF3B1) by next-generation sequencing. PFS and TTNT (AV and AVO vs FCR/BR) were calculated using an unstratified Cox proportional-hazards model. Results In total,867 pts were randomized (AV=291; AVO=286; FCR/BR=290); 57% (AV), 59% (AVO), and 59% (FCR/BR) had uIGHV; median follow-up was 40.8 mo. Mutation analysis demonstrated comparable prevalence of mutations across arms, most commonly ATM (24% AV, 24% AVO, 20% FCR/BR), NOTCH1 (14% AV, 16% AVO, 17% FCR/BR), and SF3B1 (15% AV, 16% AVO, 16% FCR/BR). Across arms, most ATM, SF3B1, and NOTCH1 mutations occurred in pts with uIGHV (AV: 71%, 78%, and 76%, respectively; AVO: 74%, 70%, 91%; FCR/BR: 73%, 80%, 86%), with significantly higher frequencies in pts with uIGHV vs mutated IGHV (mIGHV; P<0.01). Among pts with ≥1 mutation (AV=145; AVO=150; FCR/BR=137), co-mutation rates in the AV, AVO, and FCR/BR arms were ATM/NOTCH1 (6.2%, 10.0%, 10.2%), ATM/SF3B1 (12.4%, 10.0%, 10.9%), and NOTCH1/SF3B1 (5.5%, 4.7%, 8.8%), respectively. The 36-mo PFS (ITT) was 76.5% (AV), 83.1% (AVO), and 66.5% (FCR/BR). PFS improvement was observed with AV vs FCR/BR in pts with uIGHV (hazard ratio [HR] 0.69; 95% CI 0.48–0.97) and mutated ATM (0.50; 0.25–1.0), NOTCH1 (0.72; 0.36–1.42), and SF3B1 (0.22; 0.09–0.55), and with AVO vs FCR/BR (uIGHV: 0.35, 0.23–0.53; ATM: 0.41, 0.19–0.86; NOTCH1: 0.26, 0.10–0.65; SF3B1: 0.34, 0.15–0.77). Among pts with/without ATM, 36-mo PFS was 76%/74% (AV), 82%/84% (AVO), and 58%/68% (FCR/BR). Among pts with/without NOTCH1, 36-mo PFS was 57%/79% (AV), 86%/83% (AVO), and 50%/69% (FCR/BR). A 36-mo PFS rate difference in AV with/without NOTCH1 was seen in the uIGHV subgroup (49%/73%; HR 0.46; 95% CI 0.24–0.87) but not in the mIGHV subgroup (80%/85%; 0.77; 0.18–3.37); however, sample size was limited in this subgroup. For those with/without SF3B1, 36-mo PFS was 85%/74% (AV), 79%/85% (AVO), and 51%/69% (FCR/BR). The 36-mo TTNT (ITT) was 88.5% (AV), 85.4% (AVO), and 75.2% (FCR/BR). TTNT improvement for AV and AVO vs FCR/BR was observed for pts with uIGHV (HR 0.50 [95% CI 0.33–0.74] and 0.35 [0.22–0.54], respectively) and mutated ATM (0.32 [0.14–0.75] and 0.53 [0.25–1.14]), NOTCH1 (0.56 [0.24–1.29] and 0.42 [0.17–1.05]), and SF3B1 (0.24 [0.08–0.74] and 0.43 [0.17–1.09]). For those with/without ATM, 36-mo TTNT was 89%/88% (AV), 82%/88% (AVO), and 69%/77% (FCR/BR). For those with/without NOTCH1, 36-mo TTNT was 77%/90% (AV), 84%/86% (AVO), and 64%/78% (FCR/BR); for those with/without SF3B1, 36-mo TTNT was 91%/87% (AV), 85%/86% (AVO), and 68%/77% (FCR/BR). Conclusion This analysis from AMPLIFY demonstrates an association between presence of mutations and uIGHV status. Similar benefits in PFS and TTNT with AV and AVO vs FCR/BR were observed across these mutations. In the AVO arm, ATM, SF3B1, and NOTCH1 mutations were not associated with poorer outcomes. In the AV arm, pts with uIGHV without a NOTCH1 mutation had better outcomes vs patients with uIGHV with a co-occurring NOTCH1 mutation. The predictive values of these mutations will be explored via multivariate analysis.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,077
Score d'incertitude au seuil0,983

Scores Codex et Gemma par catégorie

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

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 Opus0,027
Tête enseignante GPT0,355
Écart entre enseignants0,328 · 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 tête enseignante, 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
Publié2025
Routes d'admission1
Résumé présentoui

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