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392 Validation of ELN2017 Risk Stratification in a Post-Hoc Analysis of the Prospective Biomarker-Based Gimema AML1310 Protocol

Program: Oral and Poster Abstracts
Type: Oral
Session: 613. Acute Myeloid Leukemia: Molecular Mutations and Their Prognostic Implications
Hematology Disease Topics & Pathways:
AML, Adult, Diseases, Study Population, Myeloid Malignancies, Clinically relevant
Sunday, December 6, 2020: 1:00 PM

Raffaele Palmieri, MD1*, Francesco Buccisano, MD1, Alfonso Piciocchi, MS2*, Valentina Arena, MS2*, Anna Candoni3*, Lorella MA Melillo, MD4*, Valeria Calafiore5*, Roberto Cairoli, MD6*, Paolo De Fabritiis, MD7*, Gabriella Storti8*, Prassede Salutari, MD9*, Francesco Lanza, MD10*, Giovanni Martinelli, MD11,12, Mario Luppi13*, Saveria Capria, MD14*, Luca Maurillo15*, Maria Ilaria Del Principe1*, Giovangiacinto Paterno1*, Maria Teresa Voso, MD16, Tiziana Ottone1*, Serena Lavorgna1*, Paola Fazi, MD2*, Marco Vignetti, MD17*, William Arcese, MD, PhD1,18 and Adriano Venditti, MD 1

1Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
2GIMEMA Foundation, Rome, Italy
3Hematology, Azienda Sanitaria Integrata di Udine, Udine, ITA
5Division of Hematology, Azienda Policlinico-OVE, University of Catania, Rodolico, Italy
6Department of Haematology, Niguarda Cancer Center, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
7Department of Hematology S. Eugenio Hospital, Rome, Italy, Roma, Italy
8Azienda Ospedaliera di rilievo Nazionale, S.G. Moscati, Avellino, ITA
9Bone Marrow Transplant Center, Department of Hematology, Transfusion Center and Biotechnology, Presidio Ospedaliero Spirito Santo, Pescara, Italy
10Division of Hematology, Onco-hematologic Department, AUSL della Romagna, Ravenna, Italy
11Institute of Hematology “L. e A. Seràgnoli”, Department of Experimental, Diagnostic and Specialty Medicine, Bologna, Italy
12Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori IRST IRCCS, Meldola, Italy
13Department of Medical and Surgical Sciences, Section of Hematology, University of Modena and Reggio Emilia, Modena, Italy
14Department of Translational and Precision Medicine, Sapienza University, Division of Hematology, Rome, Italy
15Hematology Department, Tor Vergata University Hospital, Rome, Italy, Rome, Italy
16University of Rome Tor Vergata, Rome, Italy
17GIMEMA Foundation, Roma, ITA
18Tor Vergata University of Rome, Rome Transplant Network, Rome, Italy

Background: In the 2017 version of the ELN recommendations (ELN2017), a comprehensive evaluation of karyotype and mutational status of specific genes (e.g. FLT3 and NPM1) allows to classify patients (pts) with Acute Myeloid Leukemia (AML) into 3 prognostically distinct risk groups (favorable, intermediate and adverse-risk). Before the publication of the ELN2017 guidelines, the Gruppo Italiano Malattie Ematologiche MAligne (GIMEMA) conducted a prospective trial (AML1310) in which prognostic classification relied on the risk assessment criteria (NCCN2009) at that time available. In this post-hoc analysis, we investigated the applicability of the ELN2017 risk stratification to the AML1310 study population.

Methods: After induction and consolidation, pts in complete remission (CR) were to receive autologous stem cell transplant (AuSCT) if categorized as favorable-risk (FR) (CBF-AML, NPM1-mutated) or allogeneic stem cell transplant (ASCT) if adverse-risk (AR) (FLT3-ITD, complex karyotype). Intermediate-risk pts (IR) were to receive AuSCT or ASCT based on the post-consolidation levels of MRD as measured by flow-cytometry. Baseline genetic/cytogenetic, together with RUNX1/RUNX1T1, CBFb/MYH11, NPM1, FLT3 mutational status (including the FLT3 allelic ratio for those positive) were used to retrospectively classify pts according to the ELN2017.

Results: All 500 pts, enrolled in the AML1310 trial, were included in the present analysis. Retrospective allocation was feasible in 445/500 (89%) cases and pts lacking crucial information for a proper ELN2017 assignment, defined a control group (ELN2017-NC). Median age was 49 (range 18-61). The re-assignmentaccording to the ELN2017, resulted in 186 pts (41.8%) belonging to the FR category (ELN2017-FR), 179 (40.2%) to the IR (ELN2017-IR) and 80 (18%) to the AR (ELN2017-AR) ones. Moreover, 55 (11%) pts were considered ELN2017-NC. Based on this process of re-assignment, 173 pts were reclassified according to ELN2017: 6 from NCCN FR (1 ELN2017-NC, 4 ELN2017-IR, 1 ELN2017-AR), 54 from NCCN IR (34 ELN2017-NC, 4 ELN2017-IR, 1 ELN2017-AR), and 113 from NCCN AR (20 ELN2017-NC, 38 ELN2017-FR, 55 ELN2017-AR) groups. After 1-2 cycles of induction, 361 (72%) pts obtained CR or CR incomplete (CRi): 163 (88.1%), 114 (65%), 45 (56.2%) and 39 (70%) in the ELN2017-FR, ELN2017-IR, ELN2017-AR and ELN2017-NC groups, respectively (p<0.001). Among 342 transplant candidates, 111/177 (82 [73.9%] ELN2017-FR, 19 [17.1%] ELN2017-IR, 2 [1.8%] ELN2017-AR, 8 [7.2%] ELN2017-NC) and 132/165 (25 [18.9%] ELN2017-FR, 61 [46.2%] ELN2017-IR, 25 [18.9%] ELN2017-AR, 21 [15.9%] ELN2017-NC) received AuSCT and ASCT, respectively (p<0.001). According to ELN2017 risk classification, the four groups significantly differed (p < 0.001) in terms of 2-years overall survival (OS) (68.8% vs. 51.3% vs. 45.8% vs. 42.8% for the ELN2017-FR, ELN2017-IR, ELN2017-NC, and ELN2017-AR groups, respectively). [Figure 1] Then, we investigated the impact of AuSCT and ASCT on each ELN2017 category; this evaluation was not possible for ELN2017-AR pts since only 2 of them received AuSCT. Among ELN2017-FR pts, a significant benefit of AuSCT over ASCT was observed (2-years OS of 83.3% vs. 66.7%, respectively; p=0.0421). In the ELN2017-IR group, AuSCT and ASCT performed equivalently (2-years OS of 73.9% vs. 70.8%, respectively). In univariate analyses, OS duration was shorter for pts from the ELN2017-AR (HR=2.203, CI 1.496-3.246; p<0.0001), ELN2017-IR (HR=1.796, CI 1.293-2-494; p=0.0005), and ELN2017-NC (HR=2.267, CI 1.488-3.228; p=0.0001). Multivariate model for OS prediction highlighted the role of age (HR=1.033, p<.0001), ELN2017 assignment and transplant (analyzed as a time-dependent covariate) (HR=0.674, p=0.0185), as the most significant prognostic variables.

Summary/Conclusion: In this GIMEMA AML1310 post-hoc analysis, we confirmed that the ELN2017 classification is able to accurately define pts that can benefit from different post-remission strategies. Specifically, AuSCT granted longer survival in FR pts, while for IR pts AuSCT and ASCT performed equally when minimal residual disease was used as a driver for opting between one of the two. In conclusion, ELN classification is a reliable grouping system that, combined with MRD assessment, helps addressing pts to the most appropriate treatment. Such an hypothesis will be prospectively challenged in the next GIMEMA trial AML1819.

Disclosures: Luppi: Sanofi: Consultancy; Gilead Sci: Consultancy, Speakers Bureau; Abbvie: Consultancy; MSD: Consultancy; Daiichi-Sankyo: Consultancy; Novartis: Consultancy, Speakers Bureau. Voso: Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Venditti: Janssen: Consultancy, Honoraria, Other: TRAVEL, ACCOMODATIONS, EXPENSES (paid by any for-profit health care company); Jazz: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); AbbVie: Consultancy, Honoraria, Other: TRAVEL, ACCOMODATIONS, EXPENSES (paid by any for-profit health care company); Amgen: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Pfizer: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Novartis: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company).

*signifies non-member of ASH