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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Hematology
2022
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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. |
format | Online Article Text |
id | pubmed-9043923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Society of Hematology |
record_format | MEDLINE/PubMed |
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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