ASC4FIRST, a pivotal phase 3 study of asciminib (ASC) vs investigator-selected tyrosine kinase inhibitors (IS TKIs) in newly diagnosed patients (pts) with chronic myeloid leukemia (CML): Primary results.
Notice bibliographique
Résumé
LBA6500 Background: We present primary results from ASC4FIRST (NCT04971226), the first study in CML comparing all current standard-of-care frontline TKIs with a novel agent, ASC, in newly diagnosed pts. ASC Specifically Targets the ABL Myristoyl Pocket (STAMP). Methods: Adults with CML were randomly assigned 1:1 to receive ASC 80 mg once daily or an IS TKI at standard label doses, stratified by ELTS risk category and prerandomization selected (PRS) TKI (imatinib [IMA] or second-generation [2G] TKIs), which was selected by investigators before randomization, accounting for pt preference. Pts diagnosed within 3 mo before enrollment with no prior treatment (Tx) except IMA/2G TKIs for ≤2 wk prior to randomization were eligible. Primary objectives were to demonstrate superior major molecular response (MMR) rate at wk 48 with ASC vs IS TKI and ASC vs IS TKI within the stratum of pts with IMA as PRS TKI (ASCIMA vs IS TKIIMA). The study is positive if either objective is met. Comparing MMR rate of ASC vs IS TKI at wk 48 within the stratum of pts with 2G TKIs as PRS TKI (ASC2G vs IS TKI2G) was an unpowered secondary objective. Results: Pts received ASC (n=201: ASCIMA, n=101; ASC2G, n=100) or IS TKI (n=204: IS TKIIMA, n=102; IS TKI2G, n=102 [nilotinib, 48%; dasatinib, 41%; bosutinib, 11%]). Median follow-up was 16.3 and 15.7 mo for ASC and IS TKI, respectively (cutoff: Nov 28, 2023). At cutoff, Tx was ongoing in 86%, 62%, and 75% of pts on ASC, IMA, and 2G TKIs, respectively, with pts most commonly discontinuing due to unsatisfactory therapeutic effect (6%, 21%, 10%) (Tx failure per ELN2020 [5%, 16%, 8%], MMR loss [0.5%, 0%, 0%], physician decision [0.5%, 5%, 2%]) and adverse events (AEs) (5%, 11%, 10%). MMR rate at wk 48 (per ITT) was superior with ASC (67.7%) vs IS TKI (49.0%) and with ASCIMA (69.3%) vs IS TKIIMA (40.2%), meeting both primary objectives with high statistical significance; rate difference was 18.9% [95% CI, 9.6%-28.2%] and 29.6% [95% CI, 16.9%-42.2%], respectively, both with adjusted 1-sided P<.001. MMR rate at wk 48 was higher with ASC2G vs IS TKI2G (66.0% vs 57.8%). BCR::ABL1IS ≤1% rate at wk 48 was 87% with ASC vs 73% with IS TKI and 84% with ASCIMA vs 62% with IS TKIIMA. At wk 48, MR4 and MR4.5 rates were higher with ASC vs IS TKI (39% vs 21%; 17% vs 9%), ASCIMA vs IS TKIIMA (43% vs 15%; 18% vs 5%), and ASC2G vs IS TKI2G (35% vs 26%; 16% vs 13%). ASC had markedly favorable safety and tolerability vs IMA and 2G TKIs, with less grade ≥3 AEs (38%, 44%, 55%), half the rate of AEs leading to Tx discontinuation (5%, 11%, 10%), and less dose adjustments/interruptions to manage AEs (30%, 39%, 53%). Rate of arterial occlusive events was 1%, 0%, and 2%, respectively. Conclusions: ASC is the only agent to show a statistically significant superior efficacy and excellent safety and tolerability vs all current standard-of-care frontline Tx, with potential to be the therapy of choice for CML. Clinical trial information: NCT04971226 .
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,002 |
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 source (Gemma direct ou Codex distillé), 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 ».