Integrating clinical features with genetic factors enhances survival prediction for adults with acute myeloid leukemia

Abstract

The 2017 European LeukemiaNet 2017 acute myeloid leukemia (AML) risk stratification (ELN2017) is widely used for risk-stratifying patients with AML. However, its applicability in low- and middle-income countries is limited because of a lack of full cytogenetic and molecular information at diagnosis. Here, we propose an alternative for risk stratification (the Adapted Genetic Risk [AGR]), which permits cytogenetic or molecular missing data while retaining prognostic power. We first analyzed 167 intensively treated patients with nonacute promyelocytic leukemia AML enrolled in São Paulo, Brazil (Faculdade de Medicina da Universidade de São Paulo), as our training data set, using ELN2017 as the standard for comparison with our AGR. Next, we combined our AGR with clinical prognostic parameters found in a Cox proportional hazards model to create a novel scoring system (survival AML score, SAMLS) that stratifies patients with newly diagnosed AML. Finally, we have used 2 independent test cohorts, Faculdade de Medicina de Ribeirão Preto (FMRP; Brazil, n = 145) and Oxford University Hospitals (OUH; United Kingdom, n = 157) for validating our findings. AGR was statistically significant for overall survival (OS) in both test cohorts (FMRP, P = .037; OUH, P = .012) and disease-free survival in FMRP (P = .04). The clinical prognostic features in SAMLS were age (>45 years), white blood cell count (<1.5 or >30.0 × 103/μL), and low albumin levels (<3.8 g/dL), which were associated with worse OS in all 3 cohorts. SAMLS showed a significant difference in OS in the training cohort (P < .001) and test cohorts (FMRP, P = .0018; OUH, P < .001). Therefore, SAMLS, which incorporates the novel AGR evaluation with clinical parameters, is an accurate tool for AML risk assessment.