Development of a Nomogram for Predicting the Cumulative Incidence of Disease Recurrence of AML After Allo-HSCT - Zhang, Tongtong; Bao, Xiebing; Qiu, Huiying; Tang, Xiaowen; Han, Yue; Fu, Chengcheng; Sun, Aining; Ruan, Changgeng; Wu, Depei; Chen, Suning; Xu, Yang (Frontiers in Oncology, 2021)
Using targeted exome sequencing, we studied correlations between mutations at diagnosis and transplant outcomes in 335 subjects with acute myeloid leukaemia (AML) receiving allotransplantation. A total of 302 patients (302/335, 90.1%) had at least one oncogenic point mutation. In multivariable analyses, disease status pre-transplant, MRD pre-transplant, cytogenetic risk classification and TP53, FLT3-ITDhigh ratio mutations were independent risk factors for AML recurrence after allotransplantation (P < 0.05). A nomogram for the cumulative incidence of relapse (CIR) that integrated all the predictors in the multivariable model was then constructed, and the concordance index (C-index) values at 6, 12, 18, and 24 months for CIR prediction were 0.754, 0.730, 0.715 and 0.690, respectively. Moreover, calibration plots showed an excellent agreement at 6 months, favorable agreement at 12 and 18 months, and an acceptable agreement between the actual observation and the nomogram prediction for the 24 months post-transplantation CIR in the internal validation. The integrated calibration index (ICI) were 0.008, 0.055, 0.094, and 0.136 at 6, 12, 18 and 24 months post-transplantation, respectively. With a median cut-off score value of 9.73 from the nomogram, all patients could be divided into two groups, and the difference in 2-year CIR, disease free survival (DFS) and overall survival (OS) between these two groups was significant (P < 0.05). Taken together, the results of our study indicate that gene mutations could help to predict the outcomes of patients with AML receiving allotransplantation.