Validation of ELN2017 Risk Stratification in a Post-Hoc Analysis of the Prospective Biomarker-Based Gimema AML1310 Protocol
Authors: Palmieri Raffaele , Buccisano Francesco , Piciocchi Alfonso , Arena Valentina , Candoni Anna , Melillo Lorella MA , 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 , Voso Maria Teresa , Ottone Tiziana , Lavorgna Serena , Fazi Paola , Vignetti Marco , Arcese William , Venditti Adriano 
Published: November 2020

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&lt;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&lt;0.001). According to ELN2017 risk classification, the four groups significantly differed (p &lt; 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&lt;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&lt;.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: Abbvie: Consultancy; Novartis: Consultancy, Speakers Bureau; Gilead Sci: Consultancy, Speakers Bureau; Sanofi: Consultancy; Daiichi-Sankyo: Consultancy; MSD: Consultancy. Voso:Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Venditti:Pfizer: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Amgen: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, 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); Janssen: Consultancy, Honoraria, Other: TRAVEL, ACCOMODATIONS, EXPENSES (paid by any for-profit health care company); Novartis: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company).