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Enregistrement W4417016071 · doi:10.1182/blood-2025-724

A comparison of real-world outcomes of asciminib versus ATP-competitive tyrosine kinase inhibitors as second-line treatment in patients with chronic myeloid leukemia in chronic phase

2025· article· en· W4417016071 sur OpenAlexaff
Ehab Atallah, Islam Mohamad Sadek, Emily McGovern, Dominick Latrémouille-Viau, Carmine Rossi, Remi Bellefleur, Nathan Gobeil, Gabriel Marquez, Annie Guérin, Daisy Yang, David Wei

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensGroup for Research in Decision Analysis
Organismes subventionnairesnon disponible
Mots-clésNilotinibMyeloid leukemiaComorbidityDasatinibTyrosine-kinase inhibitorRetrospective cohort studySorafenibImatinib mesylate

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Adenosine triphosphate (ATP)-competitivetyrosine kinase inhibitors (TKIs) are part of the current treatment landscape for Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase (CML-CP), approved by the FDA between 2006–2012 for newly diagnosed and previously-treated patients. Asciminib, a TKI that targets the ABL myristoyl pocket, received FDA approval in October 2024 for treatment of newly diagnosed or previously treated CML-CP following 2021 approval for third-line treatment or for those with T315I mutation. This study aimed to compare real-world outcomes of patients treated with asciminib versus ATP-competitive TKIs as second-line treatment (2L). Methods: This retrospective panel-based chart review study collected de-identified patient data via an online case report form between February-December 2024 (asciminib cohort), and May-June 2025 (comparison cohort) from eligible US oncologists and hematologists with experience treating CML. Adult patients with CML-CP were included if they had no T315I mutation and initiated asciminib (asciminib cohort) or a 1st- or 2nd-generation ATP-competitive TKI (comparison cohort) from January 2022–June 2023 (index) as 2L. Entropy balancing was used to adjust baseline characteristics between the two cohorts including demographics (age, sex, race/ethnicity, index year), severity at diagnosis (ECOG PS, Sokal score), first-line (1L) TKI characteristics (1st- or 2nd-generation TKI, reason for 1L TKI termination, last response on 1L TKI), and comorbidity profile at index (NCI comorbidity index). Time to discontinuation, and time to BCR::ABL1≤0.1% (MR3 or better) and BCR::ABL1≤0.01% (MR4 or better) were assessed using weighted Kaplan-Meier analyses; Wilcoxon tests were reported. Data collection is ongoing for the comparison cohort. Results: A total of 255 patients were included in the asciminib cohort, and an interim sample of 137 patients comprised the comparison cohort (dasatinib: 43.8%, nilotinib: 32.1%, bosutinib: 20.4%, imatinib: 3.6%). Data were collected from 76 physicians (community practice: 47.4%, academic center: 52.6%) for the asciminib cohort and 33 physicians (community: 36.4%, academic: 63.6%) for the comparison cohort, similarly distributed across all US census regions. After balancing, characteristics were similar between the asciminib and comparison cohorts, including median age (62.0 vs 62.0), proportion female (43.5% vs 43.8%), race/ethnicity (white: 56.1% vs 56.2%, black: 20.8% vs 20.4%), ECOG ≥2 (17.3% vs 17.5%), intermediate-high Sokal scores (76.1% vs 75.9%), and NCI comorbidity index >0 (60.0% vs 59.9%). Similar proportions of patients discontinued their 1L TKI due to intolerance (43.5% vs 43.8%) or lack of efficacy (42.4% vs 42.3%) and had a last response of MR3 or better on 1L (28.2% vs 28.5%). All standardized mean differences were ≤0.01. By 48-week post-index, 68.3% of the asciminib vs 58.1% of the comparison cohort achieved or maintained MR3 (p<0.05); and 40.6% vs 21.0% achieved or maintained MR4 (p<0.05). Median time to MR3 (MR4) was 30.7 (59.7) and 39.7 (74.0) weeks for the asciminib and comparison cohorts, respectively. By 48-week post-index, 4.6% of the asciminib vs 13.0% of the comparison cohort had discontinued treatment for any reason (p<0.05). During that period, discontinuation due to intolerance occurred in 1.6% of patients in the asciminib vs 3.6% in the comparison cohort, and discontinuation due to resistance was observed in none and 4.4% of patients, respectively. Moreover, post-index, intolerance led to temporary treatment interruption in 4.3% of patients in the asciminib vs 8.8% in the comparison cohort, and to dose reduction in 2.0% and 5.8% of patients, respectively. Dose increase due to resistance was reported only in the comparison cohort, for 5.1% of patients.Conclusions: Patients with CML-CP who received asciminib as 2L achieved deeper and faster molecular responses, with higher rates of MR3 and MR4 and shorter time to MR3, in comparison to those treated with ATP-competitive TKIs. Moreover, asciminib-treated patients experienced fewer dose adjustments and discontinuations due to intolerance or resistance similar to previously reported data from ASC4FIRST and ASCEMBL. Findings from this large real-world study suggest that asciminib offers favorable tolerability and better efficacy compared to ATP-competitive TKIs in patients with CML-CP as 2L in the US clinical practice.

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)0,003
score de la tête « metaresearch » (Gemma)0,009
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 enseignants0,003
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,009
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 GPT0,325
Écart entre enseignants0,307 · 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

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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