Prognostic Nomogram for Childhood Acute Lymphoblastic Leukemia: A Comprehensive Analysis of 673 Patients

Rui Mao; Shaoxuan Hu; Yuanchuan Zhang; Feng Du; Yu Zhang; Yanjun Liu; Tongtong Zhang

doi:10.3389/fonc.2020.01673

Prognostic Nomogram for Childhood Acute Lymphoblastic Leukemia: A Comprehensive Analysis of 673 Patients

Front Oncol. 2020 Sep 10:10:1673. doi: 10.3389/fonc.2020.01673. eCollection 2020.

Authors

Rui Mao¹, Shaoxuan Hu², Yuanchuan Zhang³, Feng Du⁴, Yu Zhang⁵, Yanjun Liu³, Tongtong Zhang⁶

Affiliations

¹ The Affiliated Hospital of Southwest Jiaotong University, Chengdu, China.
² Department of Hematology, Peking University Cancer Hospital and Institute, Beijing, China.
³ The Center of Gastrointestinal and Minimally Invasive Surgery, The Third People's Hospital of Chengdu, Chengdu, China.
⁴ Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Beijing, China.
⁵ State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Beijing, China.
⁶ Medical Research Center, The Third People's Hospital of Chengdu, The Affiliated Hospital of Southwest Jiaotong University, The Second Chengdu Hospital Affiliated to Chongqing Medical University, Chengdu, China.

Abstract

Objective: Despite that the survival rate in childhood acute lymphoblastic leukemia (cALL) is excellent, subsets of high-risk patients with cALL still have high relapse rates, and the cure rate is well below that for which we should aim. The present study aims to construct a prognostic nomogram to better inform clinical practitioners and improve risk stratification for clinical trials.

Methods: The developed nomogram was based on the therapeutically applicable research to generate effective treatment (TARGET) database. With this database, we obtained 673 cALL patients with complete clinical information. We identified and integrated significant prognostic factors to build the nomogram model by univariate and multivariate Cox analysis. The predictive accuracy and discriminative ability of the nomogram were determined by the concordance index (C-index), calibration curve, and area under the receiver operating characteristic (ROC) curve (AUC) of ROC analysis. Internal validations were assessed by the bootstrapping validation.

Results: In the multivariate analysis of the primary cohort, the independent factors for survival were ETV6 RUNX1 fusion status, karyotype, minimal residual disease (MRD) at day 29, and DNA index, which were all integrated into the nomogram. The calibration curve for the probability of survival showed good agreement between the prediction by the nomogram and the actual observation. The C-index of the nomogram for predicting survival was 0.754 (95% CI, 0.715-0.793), and the AUCs for 3-, 5-, and 7-year survival were 0.775, 0.776, and 0.772, respectively.

Conclusion: We comprehensively evaluated the risk of clinical factors associated with prognosis and carried out risk stratification. The nomogram proposed in this study objectively and accurately predicted the prognosis of children with ALL.

Keywords: childhood acute lymphoblastic leukemia; genetic predisposition; nomogram; prognosis; therapeutically applicable research to generate effective treatment database.