弥漫性大B细胞淋巴瘤预后预测模型的效能与外部验证

Effectiveness and external validation of a prognostic prediction model for diffuse large B-cell lymphoma

  • 摘要:
    目的 分析影响弥漫性大B细胞淋巴瘤(DLBCL)患者预后的相关因素, 并建立列线图预测DLBCL患者的预后。
    方法 利用美国国家癌症研究所监测、流行病学和最终结果数据库(SEER数据库)提取9 486例DLBCL患者的基线资料, 将SEER数据按照7:3比例随机分为SEER训练集6 681例和SEER验证集2 805例。采用单因素、多因素Cox回归分析确定影响DLBCL患者预后的危险因素, 并在此基础上建立列线图; 采用一致性指数(C-index)、受试者工作特征(ROC)曲线的曲线下面积(AUC)以及校准曲线评价模型的区分度及其预测效能。选取2013年1月-2017年12月本院血液内科及肿瘤科的120例DLBCL患者作为外部验证集, 对列线图进行外部验证并分析其影响因素。
    结果 多因素Cox回归分析结果显示, 年龄≥ 60岁、男性、Ann Arbor分期高、有B症状、未接受放疗、未接受化疗是影响DLBCL预后的危险因素(P < 0.05), 同时将上述因素纳入列线图模型。SEER训练集、验证集以及外部验证集的C-index分别为0.681、0.669、0.817, SEER训练集、验证集以及外部验证集ROC曲线预测DLBCL患者5年生存率的AUC分别为0.699、0.678、0.869。校准曲线显示列线图预测模型结果与实际结果具有良好的一致性。计算患者的风险评分并将其分为低风险组(< 170分)和高风险组(≥ 170分), 低风险组的5年生存率在SEER训练集、SEER验证集以及外部验证集中均为最高。
    结论 男性、年龄≥ 60岁、Ann Arbor分期高、未接受放疗、未接受化疗、存在B症状是影响DLBCL患者预后的独立危险因素。基于上述因素建立的列线图预测模型具有良好的预测效能, 可对DLBCL患者预后进行个体化风险评估和预测。

     

    Abstract:
    Objective To analyze the related factors affecting the prognosis of patients with diffuse large B-cell lymphoma (DLBCL), and to establish a Nomogram for prediction of the prognosis of patients with DLBCL.
    Methods The baseline data of 9 486 patients with DLBCL were extracted from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute, and the SEER data were randomly divided into SEER training set (n=6 681) and SEER validation set (n=2 805) according to the ratio of 7 to 3. Univariate and multivariate Cox regression analyses were used to determine the risk factors affecting the prognosis of patients with DLBCL, and on this basis, a Nomogram was established; the discrimination and prediction efficiency of the model were evaluated by consistency index (C-index), area under the curve (AUC) of receiver operating characteristic (ROC) curve and calibration curve. A total of 120 patients with DLBCL in the Department of Hematology and Department of Oncology in authors' hospital from January 2013 to December 2017 were selected as external validation set, and the external validation was performed to verify the Nomogram and analyze its influencing factors.
    Results Multivariate Cox regression analysis showed that age ≥ 60 years old, male, high stages of Ann Arbor staging, presence of B symptoms, lack of radiotherapy and lack of chemotherapy were the risk factors affecting the prognosis of DLBCL (P < 0.05), and the above factors were included in the Nomogram model. The C-index values of SEER training set, validation set and external validation set were 0.681, 0.669 and 0.817 respectively, and the AUC values of ROC curves of SEER training set, validation set and external validation set for predicting 5-year survival rate of DLBCL patients were 0.699, 0.678 and 0.869 respectively. The calibration curve showed that the result of the Nomogram prediction model was in good consistency with the actual result. Patients were divided into low-risk group (< 170 points) and high-risk group (≥ 170 points) according to the calculated risk scores, and the 5-year survival rate of the low-risk group was the highest in the SEER training set, validation set and external validation set.
    Conclusion Male, age ≥ 60 years old, high stages of Ann Arbor staging, lack of radiotherapy, lack of chemotherapy and presence of B symptoms are the independent risk factors affecting the prognosis of patients with DLBCL. The Nomogram prediction model established based on the above factors has good predictive performance, and can be used for personalized risk assessment and prediction of the prognosis of patients with DLBCL.

     

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