Zhang Dan, Cheng Yu, Fan Jia, Yao Juan, Zhao Zijun, Jiang Yao, Li Yiqin, Zuo Zhihua, Tang Yan, Guo Yongcan
Clinical Laboratory of Traditional Chinese Medicine Hospital Affiliated to Southwest Medical University, Luzhou, China.
Sichuan Luzhou Traditional Chinese Medicine Hospital, Luzhou, China.
Front Oncol. 2020 Aug 25;10:1550. doi: 10.3389/fonc.2020.01550. eCollection 2020.
Advances in treatment and supportive care have significantly improved the overall survival (OS) of pediatric patients with acute lymphoblastic leukemia (ALL). However, there is a large number of these patients who continue to relapse after receiving standard treatment. Accurate identification of patients at high risk of relapse and targeted therapy may significantly improve their prognosis. Therefore, the aim of this study was to identify significant prognostic factors for pediatric ALL and establish a novel nomogram for the prediction of survival. The ALL clinical data of Phases I and II of the Therapeutic Applicable Research to Generate Effective Treatments (TARGET) project were merged and randomly divided into training and validation groups. The LASSO regression model was used to select the specific factors related to the OS of the training group and generate prognostic nomograms according to the selected characteristics. The predictive accuracy of the nomogram for OS was verified using the concordance index of the training and validation groups, the area under the receiver operating characteristic curve for prognostic diagnosis, and the calibration curve. A total of 1,000 children with ALL were included in the TARGET project. Of those, 489 patients had complete follow-up data for further analysis. The data were randomly divided into the training group ( = 345) and the validation group ( = 144). Seven clinical characteristics, namely age at diagnosis, peripheral white blood cells, bone marrow and CNS site of relapse, ETV6/RUNX1 fusion, TCF3/PBX1, and BCR/ABL1 status, were selected to construct the nomogram. The concordance indices of the training and validation groups were 0.809 (95% confidence interval: 0.766-0.852) and 0.826 (95% confidence interval: 0.767-0.885), respectively. The areas under the receiver operating characteristic curve of the 3-year, 5-year, and 10-year OS in the training group were 0.804, 0.848, and 0.885, respectively, while that of the validation group were 0.777, 0.825, and 0.863, respectively. Moreover, the calibration curves demonstrated a favorable consistency between the predicted and actual survival probabilities. Independent predictors of OS in children with ALL included age at diagnosis, white blood cells, bone marrow site of relapse, CNS site of relapse, ETV6/RUNX1 fusion, TCF3/PBX1, and BCR/ABL1 status. The nomograms developed using these high-risk factors can more simply, accurately, and quantitatively predict the survival of children, and improve treatment and prognosis.
治疗和支持性护理方面的进展显著提高了急性淋巴细胞白血病（ALL）儿科患者的总生存期（OS）。然而，仍有大量此类患者在接受标准治疗后继续复发。准确识别复发高危患者并进行靶向治疗可能会显著改善他们的预后。因此，本研究的目的是确定小儿ALL的重要预后因素，并建立一种用于预测生存的新型列线图。将治疗适用研究以产生有效治疗方案（TARGET）项目的I期和II期ALL临床数据进行合并，并随机分为训练组和验证组。使用LASSO回归模型选择与训练组OS相关的特定因素，并根据所选特征生成预后列线图。使用训练组和验证组的一致性指数、预后诊断的受试者操作特征曲线下面积以及校准曲线来验证列线图对OS的预测准确性。TARGET项目共纳入了1000例ALL患儿。其中，489例患者有完整的随访数据用于进一步分析。数据被随机分为训练组（n = 345）和验证组（n = 144）。选择七个临床特征，即诊断时年龄、外周血白细胞、骨髓和中枢神经系统复发部位、ETV6/RUNX1融合、TCF3/PBX1以及BCR/ABL1状态，来构建列线图。训练组和验证组的一致性指数分别为0.809（95%置信区间：0.766 - 0.852）和0.826（95%置信区间：0.767 - 0.885）。训练组3年、5年和10年OS的受试者操作特征曲线下面积分别为0.804、0.848和0.885，而验证组分别为0.777、0.825和0.863。此外，校准曲线显示预测生存概率与实际生存概率之间具有良好的一致性。ALL患儿OS的独立预测因素包括诊断时年龄、白细胞、骨髓复发部位、中枢神经系统复发部位、ETV6/RUNX1融合、TCF3/PBX1以及BCR/ABL1状态。使用这些高危因素开发的列线图可以更简单、准确和定量地预测儿童的生存情况，并改善治疗和预后。
