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Enregistrement W4389233329 · doi:10.1182/blood-2023-185956

MRD Directed Treatment Intensification with Either FLAG-Ida or DA-Cladribine Improves Survival in Older AML Patients: Results from the NCRI AML18 Randomised Trial

2023· article· en· W4389233329 sur OpenAlexaff
Nigel H. Russell, Abin Thomas, Robert K. Hills, Ian Thomas, Amanda Gilkes, Nuria Marquez Almuina, Sarah S. Burns, Lucy Marsh, Georgia Andrew, Nicholas McCarthy, Jenny Byrne, Rob S. Sellar, Richard Kelly, Paul Cahalin, Ulrik Malthe Overgaard, Priyanka Mehta, Mike Dennis, Steven Knapper, Sylvie Freeman

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensAstraZeneca (Canada)
Organismes subventionnairesnon disponible
Mots-clésMedicineCytarabineInternal medicineMinimal residual diseaseCladribineDaunorubicinChemotherapyGemtuzumab ozogamicinChemotherapy regimenFlag (linear algebra)RandomizationRandomized controlled trialOncologyLeukemiaPediatricsSurgeryStem cell

Résumé

récupéré en direct d'OpenAlex

Background Following intensive chemotherapy in acute myeloid leukemia (AML), residual disease, assessed by failure to achieve a remission (CR/CRi) or the presence of measurable residual disease (MRD) in remission identifies a poor risk group of patients. In the NCRI AML16 trial for older adults (>60yrs), patients who were MRD+ve by flow cytometry in their remission bone marrow after course 1 had significantly poorer survival (26% at 3yrs vs 42% if MRD-ve) due to a higher risk of relapse (Freeman et al JCO 2016). These results suggested that flow cytometric MRD after course 1, by identifying patients who have a poor outcome with standard therapy, could be used to risk stratify for further treatment. However, although not infrequently used, it is uncertain whether chemotherapy intensification is of benefit to older adults with residual disease. In the AML18 trial we therefore conducted a course 2 randomization to evaluate MRD directed chemotherapy intensification in older adults. Methods AML18 patients who did not achieve MRD negativity after their first course (either not in CR/CRi or MRD+ve or MRD unknown) were randomized to either continue treatment with up to two courses of standard DA (Daunorubicin, AraC) (DA3+8 followed by DA2+5) or to receive up to 2 courses of intensified chemotherapy:- either FLAG-Ida or DA with Cladribine (DAC) (DA3+8, followed by DA2+5 both including Cladribine 5 mg/m 2 x 5 days). Course 1 had comprised DA (3+10) with 0, 1 or 2 doses of gemtuzumab ozogamicin. FLAG-Ida was dose reduced for patients over 70yrs and in course 3 for all patients (Fludarabine from 30mg/m 2 days 1-5 to 25mg/m 2 days 1-4, Idarubicin from 8mg/m 2 days 3-5 to 5mg/m 2 days 2-4). The DAC randomization was closed May 2019 due to drug supply issues. The primary endpoint was overall survival (OS). Rate ratios (RR) were used when appropriate to account for non-proportional hazards effect. Secondary endpoints included conversion to MRD negativity (defined as undetectable MFC-MRD) following course 2. Results Between Nov 2014 and Jan 2023, 523 patients (median age 67yrs) entered this randomization (193 DA, 191 FLAG-Ida, 139 DAC) following course 1 response assessment. Of these patients 164 (31%) were not in CR/CRi, 260 (50%) were in CR/CRi MRD+ve and the remaining 99 (19%) were in CR/CRi but with MRD unknown (due to an absence of a leukaemia-associated-immunophenotype at diagnosis or inadequate/missing samples). 99/477 (21%) of patients had adverse risk cytogenetics. All characteristics were balanced between arms. Median follow-up was 51 months. Following course 2, 47% (78/164) of those not in CR/CRi after course 1 converted to CR/CRi within 50 days: 55%, 57%, 34% for DA, DAC and FLAG-Ida respectively (DA vs DAC P=0.63, DA vs FLAG P=0.015). Of 282 patients providing MRD results after both course 1 and 2, 51% (60/117), 63% (50/79) and 58% (50/86) converted to MRD negativity after DA, DAC and FLAG-Ida respectively (DA vs DAC P=0.16, DA vs FLAG P=0.33). Greater hematological toxicity was seen with DAC or FLAG-Ida compared to DA (P<.001 for both platelet and neutrophil recovery). Day 60 mortality was increased in patients randomized to FLAG-Ida (9% vs 4% with DA and 4% with DAC, P=0.032). In total, 213 (41%) patients underwent allogeneic SCT (DA 42%, DAC 47%, Flag-Ida 35%). OS at 5yrs was 27%, 32% and 32% for DA, DAC and Flag-Ida respectively (DAC vs DA HR=0.82 95%CI 0.62-1.09, P=0.174; FLAG-Ida vs DA HR=0.90 95%CI 0.70-1.16, P=0.407). In subgroup analyses, comparing patients with known and unknown MRD status, there was no detectable survival benefit from intensification for MRD unknown patients (FLAG-Ida vs DA RR 1.52 95%CI 0.92-2.50, P value = 0.105; DAC vs DA RR 1.10, 95%CI 0.81-1.45, P value = 0.549). In a sensitivity analysis, excluding patients with unknown MRD, there was a significant OS benefit for both DAC (OS at 5yrs, 32% vs 22% for DA; RR 0.84, 95%CI 0.77-0.98, P=0.029, Figure A) and FLAG-Ida (OS at 5yrs, 34% vs 23% for DA; RR 0.71, 95%CI 0.54-0.96, P=0.026, Figure B). Conclusion In older AML patients with evidence of residual disease following first induction, we saw a significant long-term survival benefit for intensified therapy with both DAC and FLAG-Ida in a randomized comparison with DA. This was despite early toxicity, observed particularly after FLAG-Ida. DAC intensification appeared better tolerated, delivered more patients to transplant and was associated with a greater conversion to MRD negativity.

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)0,002
score de la tête « metaresearch » (Gemma)0,002
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 randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,035
Tête enseignante GPT0,290
Écart entre enseignants0,255 · 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 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

Citations5
Publié2023
Routes d'admission1
Résumé présentoui

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