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ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol

The 2017 version of the European LeukemiaNet (ELN) recommendations, by integrating cytogenetics and mutational status of specific genes, divides patients with acute myeloid leukemia into 3 prognostically distinct risk categories: favorable (ELN2017-FR), intermediate (ELN2017-IR), and adverse (ELN201...

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Autores principales: Buccisano, Francesco, Palmieri, Raffaele, Piciocchi, Alfonso, Arena, Valentina, Candoni, Anna, Melillo, Lorella, Calafiore, Valeria, Cairoli, Roberto, de Fabritiis, Paolo, Storti, Gabriella, Salutari, Prassede, Lanza, Francesco, Martinelli, Giovanni, Luppi, Mario, Capria, Saveria, Maurillo, Luca, Del Principe, Maria Ilaria, Paterno, Giovangiacinto, Irno Consalvo, Maria Antonietta, Ottone, Tiziana, Lavorgna, Serena, Voso, Maria Teresa, Fazi, Paola, Vignetti, Marco, Arcese, William, Venditti, Adriano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Hematology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043923/
https://www.ncbi.nlm.nih.gov/pubmed/34731884
http://dx.doi.org/10.1182/bloodadvances.2021005717
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author Buccisano, Francesco
Palmieri, Raffaele
Piciocchi, Alfonso
Arena, Valentina
Candoni, Anna
Melillo, Lorella
Calafiore, Valeria
Cairoli, Roberto
de Fabritiis, Paolo
Storti, Gabriella
Salutari, Prassede
Lanza, Francesco
Martinelli, Giovanni
Luppi, Mario
Capria, Saveria
Maurillo, Luca
Del Principe, Maria Ilaria
Paterno, Giovangiacinto
Irno Consalvo, Maria Antonietta
Ottone, Tiziana
Lavorgna, Serena
Voso, Maria Teresa
Fazi, Paola
Vignetti, Marco
Arcese, William
Venditti, Adriano
author_facet Buccisano, Francesco
Palmieri, Raffaele
Piciocchi, Alfonso
Arena, Valentina
Candoni, Anna
Melillo, Lorella
Calafiore, Valeria
Cairoli, Roberto
de Fabritiis, Paolo
Storti, Gabriella
Salutari, Prassede
Lanza, Francesco
Martinelli, Giovanni
Luppi, Mario
Capria, Saveria
Maurillo, Luca
Del Principe, Maria Ilaria
Paterno, Giovangiacinto
Irno Consalvo, Maria Antonietta
Ottone, Tiziana
Lavorgna, Serena
Voso, Maria Teresa
Fazi, Paola
Vignetti, Marco
Arcese, William
Venditti, Adriano
author_sort Buccisano, Francesco
collection PubMed
description The 2017 version of the European LeukemiaNet (ELN) recommendations, by integrating cytogenetics and mutational status of specific genes, divides patients with acute myeloid leukemia into 3 prognostically distinct risk categories: favorable (ELN2017-FR), intermediate (ELN2017-IR), and adverse (ELN2017-AR). We performed a post hoc analysis of the GIMEMA (Gruppo Italiano Malattie EMatologiche dell’Adulto) AML1310 trial to investigate the applicability of the ELN2017 risk stratification to our study population. In this trial, after induction and consolidation, patients in complete remission were to receive an autologous stem cell transplant (auto-SCT) if categorized as favorable risk or an allogeneic stem cell transplant (allo-SCT) if adverse risk. Intermediate-risk patients were to receive auto-SCT or allo-SCT based on the postconsolidation levels of measurable residual disease as measured by using flow cytometry. Risk categorization was originally conducted according to the 2009 National Comprehensive Cancer Network recommendations. Among 500 patients, 445 (89%) were reclassified according to the ELN2017 criteria: ELN2017-FR, 186 (41.8%) of 455; ELN2017-IR, 179 (40.2%) of 445; and ELN2017-AR, 80 (18%) of 455. In 55 patients (11%), ELN2017 was not applicable. Two-year overall survival (OS) was 68.8%, 51.3%, 45.8%, and 42.8% for the ELN2017-FR, ELN2017-IR, ELN2017-not classifiable, and ELN2017-AR groups, respectively (P < .001). When comparing the 2 different transplant strategies in each ELN2017 risk category, a significant benefit of auto-SCT over allo-SCT was observed among ELN2017-FR patients (2-year OS of 83.3% vs 66.7%; P = .0421). The 2 transplant procedures performed almost equally in the ELN2017-IR group (2-year OS of 73.9% vs 70.8%; P = .5552). This post hoc analysis of the GIMEMA AML1310 trial confirms that the ELN2017 classification is able to accurately discriminate patients with different outcomes and who may benefit from different transplant strategies. This trial was registered as EudraCT number 2010-023809-36 and at www.clinicaltrials.gov as #NCT01452646.
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spelling pubmed-90439232022-04-28 ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol Buccisano, Francesco Palmieri, Raffaele Piciocchi, Alfonso Arena, Valentina Candoni, Anna Melillo, Lorella Calafiore, Valeria Cairoli, Roberto de Fabritiis, Paolo Storti, Gabriella Salutari, Prassede Lanza, Francesco Martinelli, Giovanni Luppi, Mario Capria, Saveria Maurillo, Luca Del Principe, Maria Ilaria Paterno, Giovangiacinto Irno Consalvo, Maria Antonietta Ottone, Tiziana Lavorgna, Serena Voso, Maria Teresa Fazi, Paola Vignetti, Marco Arcese, William Venditti, Adriano Blood Adv Myeloid Neoplasia The 2017 version of the European LeukemiaNet (ELN) recommendations, by integrating cytogenetics and mutational status of specific genes, divides patients with acute myeloid leukemia into 3 prognostically distinct risk categories: favorable (ELN2017-FR), intermediate (ELN2017-IR), and adverse (ELN2017-AR). We performed a post hoc analysis of the GIMEMA (Gruppo Italiano Malattie EMatologiche dell’Adulto) AML1310 trial to investigate the applicability of the ELN2017 risk stratification to our study population. In this trial, after induction and consolidation, patients in complete remission were to receive an autologous stem cell transplant (auto-SCT) if categorized as favorable risk or an allogeneic stem cell transplant (allo-SCT) if adverse risk. Intermediate-risk patients were to receive auto-SCT or allo-SCT based on the postconsolidation levels of measurable residual disease as measured by using flow cytometry. Risk categorization was originally conducted according to the 2009 National Comprehensive Cancer Network recommendations. Among 500 patients, 445 (89%) were reclassified according to the ELN2017 criteria: ELN2017-FR, 186 (41.8%) of 455; ELN2017-IR, 179 (40.2%) of 445; and ELN2017-AR, 80 (18%) of 455. In 55 patients (11%), ELN2017 was not applicable. Two-year overall survival (OS) was 68.8%, 51.3%, 45.8%, and 42.8% for the ELN2017-FR, ELN2017-IR, ELN2017-not classifiable, and ELN2017-AR groups, respectively (P < .001). When comparing the 2 different transplant strategies in each ELN2017 risk category, a significant benefit of auto-SCT over allo-SCT was observed among ELN2017-FR patients (2-year OS of 83.3% vs 66.7%; P = .0421). The 2 transplant procedures performed almost equally in the ELN2017-IR group (2-year OS of 73.9% vs 70.8%; P = .5552). This post hoc analysis of the GIMEMA AML1310 trial confirms that the ELN2017 classification is able to accurately discriminate patients with different outcomes and who may benefit from different transplant strategies. This trial was registered as EudraCT number 2010-023809-36 and at www.clinicaltrials.gov as #NCT01452646. American Society of Hematology 2022-04-18 /pmc/articles/PMC9043923/ /pubmed/34731884 http://dx.doi.org/10.1182/bloodadvances.2021005717 Text en © 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.
spellingShingle Myeloid Neoplasia
Buccisano, Francesco
Palmieri, Raffaele
Piciocchi, Alfonso
Arena, Valentina
Candoni, Anna
Melillo, Lorella
Calafiore, Valeria
Cairoli, Roberto
de Fabritiis, Paolo
Storti, Gabriella
Salutari, Prassede
Lanza, Francesco
Martinelli, Giovanni
Luppi, Mario
Capria, Saveria
Maurillo, Luca
Del Principe, Maria Ilaria
Paterno, Giovangiacinto
Irno Consalvo, Maria Antonietta
Ottone, Tiziana
Lavorgna, Serena
Voso, Maria Teresa
Fazi, Paola
Vignetti, Marco
Arcese, William
Venditti, Adriano
ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol
title ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol
title_full ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol
title_fullStr ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol
title_full_unstemmed ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol
title_short ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol
title_sort eln2017 risk stratification improves outcome prediction when applied to the prospective gimema aml1310 protocol
topic Myeloid Neoplasia
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043923/
https://www.ncbi.nlm.nih.gov/pubmed/34731884
http://dx.doi.org/10.1182/bloodadvances.2021005717
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