MétaCan
Menu
← Retour à la cohorte
Enregistrement W4405039859 · doi:10.1182/blood-2024-204004

Real-World Experience with CPX-351 for Secondary Acute Myeloid Leukemia: Comparison with FLAG-IDA in a Propensity Score Matching Analysis

2024· article· en· W4405039859 sur OpenAlexaffabout
María Agustina Perusini, Claire Andrews, Eshetu G. Atenafu, Sarit Assouline, Joseph Brandwein, Mohammad Jarrar, Steven M. Chan, Signy Chow, Dina Khalaf, Vikas Gupta, Dawn Maze, Mark D. Minden, Gizelle Popradi, Waleed Sabry, Lalit Saini, David Sanford, Lynn Savoie, Aaron D. Schimmer, Andre C. Schuh, Karen Yee, Hassan Sibai

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensUniversity of British ColumbiaLondon Health Sciences CentreUniversity Health NetworkWindsor Regional HospitalHealth Sciences CentreJuravinski Cancer CentreJewish General HospitalSunnybrook Health Science CentreUniversity of AlbertaUniversity of CalgaryVancouver General HospitalPrincess Margaret Cancer CentreMcGill University
Organismes subventionnairesnon disponible
Mots-clésFlag (linear algebra)Propensity score matchingMyeloid leukemiaMedicineInternal medicineMatching (statistics)OncologyMathematicsPathology

Résumé

récupéré en direct d'OpenAlex

CPX-351 is approved for therapy-related acute myeloid leukemia (t-AML), and AML with myelodysplastic-related changes (AML-MRC). This approval was based on improved survival, remission rates, and similar safety compared to 7+3 regimen. In clinical practice, FLAG-IDA, followed by Allogenic Stem Cell transplant (ASCT) is an acceptable approach for this group of patients (pts). Evaluating real-world data on CPX compared to FLAG-IDA, and identifying which pts might benefit most from either treatment, is crucial for optimizing treatment decisions. Aims To report real-world outcomes of CPX vs FLAG-IDA in terms of Overall Survival (OS), Leukemia-free Survival (LFS), and complete remission (CR), and to determine if mutational profiles can predict responses. Methods Patients aged 18+ meeting WHO criteria for t-AML and AML-MRC with next-generation sequencing (NGS) profiles were included. Data were collected from 10 Canadian centers for CPX and the Princess Margaret Cancer Centre for FLAG-IDA. A total of 76 patients treated with CPX and 95 with FLAG-IDA were identified. Propensity Score Matching (PSM) was used to adjust for baseline differences between the two treatment groups. Key pre-treatment variables included: age, complex cytogenetics, and TP53 mutational status. PSM resulted in 92 pts (46 case-control pairs) with a caliper difference within 0.2. Results Significant differences between pts treated with different approaches were mitigated when PSM was applied. The median number of frequently detected somatic mutations was 2 (range: 1-8), with the most common mutations being RUNX1 (n=19), ASXL1 (n=20), DNMT3A (n=20), and TET2 (n=18). In the PSM-selected population (n=92), the median follow-up time was 303 days (range: 22-1488). CR rates were higher with FLAG-IDA, with CR achieved in 27 (61%) pts treated with CPX-351 compared to 38 (82%) pts treated with FLAG-IDA (p=0.024). This finding did not translate into significantly higher rates of ASCT. Overall, 18 (41%) pts in the CPX group and 24 (52%) pts in the FLAG-IDA group proceeded with ASCT (p=0.28), corresponding to 55% and 52% of the pts who achieved CR1 after first induction (p=0.81). Assessment of mutations and their biological pathways showed that pts with ASXL1 mutations had higher CR rates with FLAG-IDA (90%) compared to CPX (50%) (p=0.046). Activating signaling (AS) mutations also showed better CR rates with FLAG-IDA (100%) vs. CPX (70%) (p=0.04). The overall 1-year OS was 52.2% (95% CI: [40.5-62.6]). There were no significant differences in outcomes when comparing CPX with FLAG-IDA. For pts treated with CPX, the 1-year OS was 56.4% [39.6-70.2], compared to 49.4% [33.3-63.5] for those treated with FLAG-IDA (p=0.73, HR: 1.10 [0.60-2.1]). The 1-year LFS was 40% [25.6-55.4] for the CPX-351 group and 46.30% [30.8-60.5] for the FLAG-IDA group (p=0.59, HR: 0.86, [0.50-1.5]. When censoring OS for transplant, the 1-year OS was 52.8% [32.0-69.9] for CPX and 47.8% [23.9-68.4] for FLAG-IDA (p=0.55, HR: 0.79 [0.37-1.7]. Pts who underwent ASCT had significantly better OS (p=0.003). However, there was no significant OS difference between ASCT preceded by FLAG-IDA or CPX(p=0.08). Specifically, for pts who had ASCT, the 1-year OS was 78% [47.0-92.7] for CPX and 58% [35.0-75.9] for FLAG-IDA. Considering pts characteristics, type of mutations, or biological pathways involved, the only subgroup that demonstrated a difference in OS when comparing CPX with FLAG-IDA was the presence of tumor suppressor gene mutations (TS=TP53+PHF6, n=17). Pts with these mutations showed higher survival in the uni and multivariable analysis when treated with CPX; the 1-year survival rate for pts treated with CPX was 25% [3.7-55.8], compared to 13% [0.7-44] for those treated with FLAG-IDA (HR 3.11 [1.4-6.9], p<0.001). No other factors showed significant differences between treatments. Conclusions We used PSM to effectively minimize differences in pts characteristics. Although FLAG-IDA was associated with higher CR rates, particularly in pts with ASXL1 mutations and, AS mutations, this did not translate into higher ASCT rates, improved OS or LFS. The only subgroup that showed a difference in OS in favor of CPX was the one with TS gene mutations.These results should be interpreted with caution due to the small pt numbers. Data regarding the reasons for not proceeding with ASCT were not available. Future research will focus on expanding the cohort and evaluating adverse events

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)0,006
score de la tête « metaresearch » (Gemma)0,010
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 seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
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 Opus0,034
Tête enseignante GPT0,317
Écart entre enseignants0,284 · 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
Publié2024
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueBlood→Même sujetAcute Myeloid Leukemia Research→Travaux en français237 207→