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Enregistrement W2987093888 · doi:10.1182/blood-2019-130263

CPX-351 As First Intensive Therapy for Elderly Patients with AML

2019· article· en· W2987093888 sur OpenAlexaboutno aff
Ellen K. Ritchie, Sumaiya Miah, Sangmin Lee, Tania J. Curcio, Pinkal Desai, Jeffrey Ball, Michael Samuel, Gail J. Roboz

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineInternal medicineCytarabineClinical endpointOncologyLeukemiaPerformance statusCancerRandomized controlled trial

Résumé

récupéré en direct d'OpenAlex

Background Acute myeloid leukemia (AML) in elderly patients is a poor prognosis disease due to many factors that include disease biology, high risk of treatment-related mortality, co-morbid illnesses, geriatric syndromes, and psychosocial factors such as cognitive decline and social isolation. Such factors make it difficult to administer intensive chemotherapy regimens needed to achieve a durable response in older patients with AML. CPX-351, Vyxeos®, is a fixed combination of the antineoplastic drugs cytarabine and daunorubicin, encased together inside the liposome in a 5:1 molar ratio. CPX-351 preferentially targets leukemic cells to a greater degree than non-leukemic cells in the bone marrow, leading to decreased cytotoxicity against normal hematopoietic cells. Methods Thirty newly-diagnosed AML patients aged ≥65yrs, without upper age limit restriction, were treated with CPX-351 as a first intensive therapy (Table 1). The primary efficacy endpoint was overall survival (OS) and the primary safety endpoint was 30-day mortality. Secondary efficacy endpoints included response rate and duration of response and assessment of the relationship between cognitive function, quality of life, and treatment outcome. Cognitive function was measured using the Montreal Cognitive Assessment (MOCA) and the Blessed Orientation-Memory-Concentration (BOMC) tests. Quality of life was assessed using the Functional Assessment of Cancer Treatment- Leukemia (FACT-Leu) questionnaire. Results Eleven patients (36.6%) achieved complete remission (CR) and 5 patients (16.6%) achieved complete remission with incomplete platelet recovery (CRi). Of these patients, 8 (26.6%) received stem cell transplants. 2 patients (6.6%) died within 30-days. Of the patients who achieved CR/CRi, 5 (16.6%) relapsed after a median remission duration of 120 days. OS at Day-30 was 93.3% and at Day-60 was 86.6%. Median OS for all patients was 14.5 months (Figure 1). Median event-free survival for all patients (defined as the time from Day 1 of treatment to persistent disease (PD) or death) has not been met at 20 months. Patients who had received prior low intensity therapy (n=16) versus those who were treatment naïve (n=14) had a significantly decreased OS (p= 0.027) (Figure 2). Median OS for previously treated patients was 5.6 months, in contrast to treatment naïve patients, who have not met median OS at 20 months. Patients who had received prior low intensity therapy also had a lower CR+CRi rate of 31.5%, in comparison to treatment naïve patients who had a CR+CRi rate of 78.5%. The most common adverse events attributable to CPX-351 were Grade 1-2 rash (20 patients, 66.7%) and Grade 2-3 decrease in left ventricular ejection fraction (LVEF) (6 patients, 20%) (Table 2). Of patients who experienced a decrease in LVEF, 5 recovered to baseline after a median of 59 days. There was a significant increase in BOMC score from baseline (BL) to the end of the first induction (EOI) (p=0.029) (Figure 3) for 29 patients. There was also a non-significant increase in the total MOCA score from BL to EOI (p=0.056) (Figure 3) for 29 patients. In addition, there was an expected overall upward trend in total FACT-Leu score from BL to EOI (n=19). There was also an upward trend in total FACT-Leu score from BL to EOI in patients who achieved CR/CRi (n=12). In contrast, there was a downward trend in total FACT-Leu score from BL to EOI in patients with PD (n=7) (Figure 4). Conclusion: Elderly AML patients can be treated safely with CPX-351 with a low 30-day mortality, a CR+CRi rate of 53.3%, and a prolonged duration of treatment response with median EFS not met at 20m. Although sample sizes for questionnaire data were small, the observed trends toward improved BOMC, MOCA, and FACT-Leu scores suggest that there may be functional cognitive improvement and improved quality of life for elderly patients treated with CPX-351. Disclosures Ritchie: Genentech: Other: Advisory board; Tolero: Other: Advisory board; Pfizer: Other: Advisory board, travel support; agios: Other: Advisory board; Celgene: Other: Advisory board; Jazz Pharmaceuticals: Research Funding; Celgene, Novartis: Other: travel support; AStella, Bristol-Myers Squibb, Novartis, NS Pharma, Pfizer: Research Funding; Ariad, Celgene, Incyte, Novartis: Speakers Bureau; Celgene, Incyte, Novartis, Pfizer: Consultancy. Lee:Helsinn: Consultancy; Jazz Pharmaceuticals, Inc: Consultancy; Roche Molecular Systems: Consultancy; AstraZeneca Pharmaceuticals: Consultancy; Karyopharm Therapeutics: Consultancy; Ai Therapeutics: Research Funding. Desai:Cellerant: Consultancy; Astex: Research Funding; Astellas: Honoraria; Sanofi: Consultancy; Celgene: Consultancy. Roboz:Sandoz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Trovagene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Orsenix: Consultancy, Membership on an entity's Board of Directors or advisory committees; Otsuka: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Eisai: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celltrion: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amphivena: Consultancy, Membership on an entity's Board of Directors or advisory committees; Argenx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Actinium: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astex: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
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)0,0010,000

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 Opus0,011
Tête enseignante GPT0,263
Écart entre enseignants0,252 · 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'étudeEssai non randomisé
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

Citations6
Publié2019
Routes d'admission1
Résumé présentoui

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