Evidence map›Paper›PMID 34731884›Full record

Trial reportBlood advances2022

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

Francesco Buccisano, Raffaele Palmieri, Alfonso Piciocchi, Valentina Arena, Anna Candoni, Lorella Melillo, Valeria Calafiore, Roberto Cairoli, Paolo de Fabritiis, Gabriella Storti and 16 more

Registry-linked trialOpen access · goldAbstract readClinical Trial
In one paragraph

Trial report in Blood advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01452646 (Risk-adapted, MRD-directed Therapy for Young Adults With Newly Diagnosed Acute Myeloid Leukemia. GIMEMA Protocol AML1310. EudraCT Number 2010-023809-36), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT01452646 phase2completednot on this map

Risk-adapted, MRD-directed Therapy for Young Adults With Newly Diagnosed Acute Myeloid Leukemia. GIMEMA Protocol AML1310. EudraCT Number 2010-023809-36

TypeinterventionalSponsorGruppo Italiano Malattie EMatologiche dell'AdultoRan2012 to 2018Enrolled515ConditionsAcute Myeloid LeukemiaArmsRisk-adapted, MRD-directed therapy
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors at 13 institutions in 1 country.

Francesco BuccisanoHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.ORCID 0000-0003-4320-9253
Raffaele PalmieriHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.ORCID 0000-0003-2855-8121
Alfonso PiciocchiGIMEMA Foundation, Rome, Italy.ORCID 0000-0001-8648-885X
Valentina ArenaGIMEMA Foundation, Rome, Italy.ORCID 0000-0003-2782-2752
Anna CandoniHematology, Azienda Sanitaria Universitaria Integrata di Udine, Udine, Italy.
Lorella MelilloFondazione IRCCS Casa Sollievo della Sofferenza, UO di Ematologia, San Giovanni Rotondo (FG), Italy.
Valeria CalafioreOspedale Ferrarotto, Catania, Italy.
Roberto CairoliOspedale Niguarda Ca Granda, Milan, Italy.
Paolo de FabritiisOspedale S. Eugenio, Rome, Italy.ORCID 0000-0002-1835-0581
Gabriella StortiAzienda Ospedaliera S.G. Moscati, Avellino, Italy.
Prassede SalutariAzienda USL di Pescara, Pescara, Italy.
Francesco LanzaOspedale S. Maria delle Croci, Ravenna, Italy.
Giovanni MartinelliIstituto Tumori della Romagna, Meldola, Italy.
Mario LuppiEmatologia, Dipartimento di Scienza Mediche e Chirurgiche Materno-Infantili e dell'Adulto, Università degli studi di Modena e Reggio Emilia, Modena, Italy.
Saveria CapriaDipartimento di Biotecnologie Cellulari ed Ematologia, Ematologia Università degli Studi Sapienza, Rome, Italy; and.
Luca MaurilloHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.ORCID 0000-0001-7297-4988
Maria Ilaria Del PrincipeHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.
Giovangiacinto PaternoHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.ORCID 0000-0002-8944-0795
Maria Antonietta Irno ConsalvoHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.
Tiziana OttoneHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.
Serena LavorgnaHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.
Maria Teresa VosoHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.ORCID 0000-0002-6164-4761
Paola FaziGIMEMA Foundation, Rome, Italy.
Marco VignettiGIMEMA Foundation, Rome, Italy.
William ArceseHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.
Adriano VendittiHematology, Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.ORCID 0000-0002-0245-0553
University of Rome Tor Vergata · ITFondazione Gimema Onlus · ITAzienda Ospedaliera S.Giuseppe Moscati · ITAzienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda · ITAzienda USL di Pescara · ITCasa Sollievo della Sofferenza · ITFerrarotto Hospital · ITIRCCS Azienda Ospedliero-Universitaria di Bologna Policlinico di Sant'Orsola · ITOspedale Santa Maria della Misericordia di Udine · ITOspedale "Santa Maria delle Croci" di Ravenna · ITSapienza University of Rome · ITSt. Eugenio Hospital · ITUniversity of Modena and Reggio Emilia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Transplantation, HomologousHumansNeoplasm, ResidualPrognosisProspective StudiesRisk Assessment

Identifiers

PMID34731884
PMCPMC9043923
OpenAlexW3209675975

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.