Individualized prediction of leukemia-free survival after autologous stem cell transplantation in acute myeloid leukemia.

Abstract

Autologous stem cell transplantation (ASCT) is a potential consolidation therapy for acute myeloid leukemia (AML). This study was designed to develop a prediction model for leukemia-free survival (LFS) in a cohort of patients with de novo AML treated with ASCT during their first complete remission. This was a registry study of 956 patients reported to the European Society for Blood and Marrow Transplantation. The primary outcome was LFS. Multivariate Cox regression modeling with backward selection was used to select variables for the construction of the nomogram. The nomogram's performance was evaluated with discrimination (the area under the receiver operating characteristic curve [AUC]) and calibration. Age and cytogenetic risk (with or without FMS-like tyrosine kinase 3 internal tandem duplication) were predictive of LFS and were used for the construction of the nomogram. Each factor in the nomogram was ascribed points according to its predictive weight. Through the calculation of the total score, the probability of LFS at 1, 3, and 5years for each patient could be estimated. The discrimination of the nomogram, measured as the AUC, was 0.632 (95% confidence interval [CI], 0.595-0.669), 0.670 (95% CI, 0.635-0.705), and 0.687 (95% CI, 0.650-0.724), respectively. Further validation with bootstrapping showed similar AUCs (0.629 [95% CI, 0.597-0.657], 0.667 [95% CI, 0.633-0.699], and 0.679 [95% CI, 0.647-0.712], respectively), and this suggested that the model was not overfitted. Calibration was excellent. Patients were stratified into 4 incremental 5-year prognostic groups, with the probabilities of LFS and overall survival ranging from 25% to 64% and from 33% to 79%, respectively. The Auto-AML nomogram score is a tool integrating individual prognostic factors to provide a probabilistic estimation of LFS after ASCT for patients with AML.