A Nomogram for Predicting Event-Free Survival in Childhood Acute Lymphoblastic Leukemia: A Multicenter Retrospective Study - He, Yun-yan; Wu, Xiao-jing; Zhou, Dun-hua; Yang, Li-hua; Mai, Hui-rong; Wan, Wu-qing; Luo, Xue-qun; Zheng, Min-cui; Zhang, Jun-lin; Ye, Zhong-lv; Chen, Hui-qin; Chen, Qi-wen; et al. (Frontiers in Oncology, 2022)
Objective: Even though childhood acute lymphoblastic leukemia (ALL) has an encouraging survival rate in recent years, some patients are still at risk of relapse or even death. Therefore, we aimed to construct a nomogram to predict event-free survival (EFS) in patients with ALL. Method: Children with newly diagnosed ALL between October 2016 and July 2021 from 18 hospitals participating in the South China children’s leukemia Group (SCCLG) were recruited and randomly classified into two subsets in a 7:3 ratio (training set, n=1187; validation set, n=506). Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were adopted to screen independent prognostic factors. Then, a nomogram can be build based on these prognostic factors to predict 1-, 2-, and 3-year EFS. Concordance index (C-index), area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance and clinical utility of nomogram. Result: The parameters that predicted EFS were age at diagnosis, white blood cell at diagnosis, immunophenotype, ETV6-RUNX1/TEL-AML1 gene fusion, bone marrow remission at day 15, and minimal residual disease at day 15. The nomogram incorporated the six factors and provided C-index values of 0.811 [95% confidence interval (CI) = 0.792-0.830] and 0.797 (95% CI = 0.769-0.825) in the training and validation set, respectively. The calibration curve and AUC revealed that the nomogram had good ability to predict 1-, 2-, and 3-year EFS. DCA also indicated that our nomogram had good clinical utility. Kaplan–Meier analysis showed that EFS in the different risk groups stratified by the nomogram scores was significant differentiated. Conclusion: The nomogram for predicting EFS of children with ALL has good performance and clinical utility. The model could help clinical decision-making.