Zhong Qiaofeng, Shi Yuankai
Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, Beijing, China.
Front Oncol. 2021 Jan 14;10:582567. doi: 10.3389/fonc.2020.582567. eCollection 2020.
Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogenous disease. Identifying more precise and individual survival prognostic models are still needed. This study aimed to develop a predictive nomogram and a web-based survival rate calculator that can dynamically predict the long-term cancer-specific survival (CSS) of DLBCL patients. A total of 3,573 eligible patients with DLBCL from 2004 to 2015 were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The entire group was randomly divided into the training (n = 2,504) and validation (n = 1,069) cohorts. We identified six independent predictors for survival including age, sex, marital status, Ann Arbor stage, B symptom, and chemotherapy, which were used to construct the nomogram and the web-based survival rate calculator. The C-index of the nomogram was 0.709 (95% CI, 0.692-0.726) in the training cohort and 0.700 (95% CI, 0.671-0.729) in the validation cohort. The AUC values of the nomogram for predicting the 1-, 5-, and 10- year CSS rates ranged from 0.704 to 0.765 in both cohorts. All calibration curves revealed optimal consistency between predicted and actual survival. A risk stratification model generated based on the nomogram showed a favorable level of predictive accuracy compared with the IPI, R-IPI, and Ann Arbor stage in both cohorts according to the AUC values (training cohort: 0.715 0.676, 0.652, and 0.648; validation cohort: 0.695 0.692, 0.657, and 0.624) and K-M survival curves. In conclusion, we have established and validated a novel nomogram risk stratification model and a web-based survival rate calculator that can dynamically predict the long-term CSS in DLBCL, which revealed more discriminative and predictive accuracy than the IPI, R-IPI, and Ann Arbor stage in the rituximab era.
弥漫性大B细胞淋巴瘤（DLBCL）是一种生物学和临床特征均具有异质性的疾病。目前仍需要确定更精确、个体化的生存预后模型。本研究旨在开发一种预测列线图和基于网络的生存率计算器，以动态预测DLBCL患者的长期癌症特异性生存（CSS）情况。从监测、流行病学和最终结果（SEER）数据库中提取了2004年至2015年期间共3573例符合条件的DLBCL患者。将整个队列随机分为训练组（n = 2504）和验证组（n = 1069）。我们确定了六个独立的生存预测因素，包括年龄、性别、婚姻状况、Ann Arbor分期、B症状和化疗情况，并用这些因素构建了列线图和基于网络的生存率计算器。训练组中列线图的C指数为0.709（95%CI，0.692 - 0.726），验证组中为0.700（95%CI，0.671 - 0.729）。在两个队列中，列线图预测1年、5年和10年CSS率的AUC值范围为0.704至0.765。所有校准曲线均显示预测生存与实际生存之间具有最佳一致性。根据AUC值（训练组：0.715对0.676、0.652和0.648；验证组：0.695对0.692、0.657和0.624）以及K-M生存曲线，基于列线图生成的风险分层模型在两个队列中均显示出与国际预后指数（IPI）、修订的国际预后指数（R-IPI）和Ann Arbor分期相比更优的预测准确性。总之，我们已经建立并验证了一种新型的列线图风险分层模型和基于网络的生存率计算器，其能够动态预测DLBCL患者的长期CSS情况，在利妥昔单抗时代，该模型显示出比IPI、R-IPI和Ann Arbor分期更高的判别能力和预测准确性。
