AML risk stratification models utilizing ELN-2017 guidelines and additional prognostic factors: a SWOG report

Era L Pogosova-Agadjanyan,Qing Zhang,I-Ming L Chen,Isaac C Jenkins,Min Fang,John Godwin ,Jerald P Radich,Thomas R Chauncey,Frederick R Appelbaum,Jasmine Naru,Emily A Stevens ,Mike Huynh,Brent L Wood,Alan F List,Anna Moseley,Brooke E Willborg,Kenneth J Kopecky,Harry P Erba,Cheryl L Willman,Megan Othus,Soheil Meshinchi,Derek L Stirewalt

doi:10.1186/s40364-020-00208-1

Abstract

BackgroundThe recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice.MethodsIn order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, N = 185) who received intensive chemotherapy. Models were validated in an independent set of similarly treated patients (validation cohort, N = 166).ResultsModels using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age < 55) than for older patients. Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models excluding results for ASXL1, CEBPA, RUNX1 and TP53, demonstrated that these mutations provide a limited overall contribution to risk stratification across the entire population, given the low frequency of mutations and confounding risk factors.ConclusionsWhile European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification.

Highlights

The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies
While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification
Given that clinical assays for ASXL1, CEBPA, RUNX1 and TP53 are not available at every institution, we examined the performance of models without the mutation status of these four genes (ELN2017-MOD)

Summary

Introduction

The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. The recently revised European LeukemiaNet (ELN-2017) recommendations for diagnosis and management of adult patients with acute myeloid leukemia (AML) are broadly accepted by physicians as a gold standard and provide guidelines to stratify patients into three outcome groups: favorable, intermediate, and adverse based on cytogenetics and mutation status of ASXL1, CEBPA, FLT3, NPM1, RUNX1, and TP53 [1]. This stratification scheme provides a simple, yet powerful means to triage patients for appropriate therapies. Studies are needed to determine if examining a more homogenous population of malignant cells may improve the precision of risk stratification guidelines, and these studies, including those examining the current ELN-2017 guidelines, need to be extended to older patients [5, 9,10,11,12]

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