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, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fujian Provincial Key Laboratory of Translational Cancer Medicine, 420 Fuma Road, Fuzhou, 350014, China.
Ann Hematol. 2024 Jan;103(1):211-226. doi: 10.1007/s00277-023-05491-0. Epub 2023 Oct 20.
This study aimed to develop and validate a novel risk stratification model and a web-based survival rate calculator to improve discriminative and predictive accuracy for diffuse large B-cell lymphoma (DLBCL) in the rituximab era.
We retrospectively collected pre-treatment data from 873 primary DLBCL patients who received R-CHOP-based immunochemotherapy regimens at the Cancer Hospital, Chinese Academy of Medical Sciences, from January 1, 2005, to December 31, 2018. An independent cohort of 175 DLBCL patients from Fujian Cancer Hospital was used for external validation.
Age, ECOG PS, number of extranodal sites, Ann Arbor stage, bulky disease, and LDH levels were screened to develop the nomogram and web-based survival rate calculator. The C-index of the nomogram in the training, internal validation, and external validation cohorts was 0.761, 0.758, and 0.768, respectively. The risk stratification model generated based on the nomogram effectively stratified patients into three distinct risk groups. K-M survival curves demonstrated that the novel risk stratification model exhibited a superior level of predictive accuracy compared to IPI, R-IPI, and NCCN-IPI both in training and two validation cohorts. Additionally, the area under the curve (AUC) value of the novel model (0.763) for predicting 5-year overall survival rates was higher than those of IPI (0.749), R-IPI (0.725), and NCCN-IPI (0.727) in the training cohort. Similar results were observed in both internal and external validation cohort.
In conclusion, we have successfully developed and validated a novel risk stratification model and a web-based survival rate calculator that demonstrated superior discriminative and predictive accuracy compared to IPI, R-IPI, and NCCN-IPI in the rituximab era.
本研究旨在开发和验证一种新的风险分层模型和基于网络的生存率计算器,以提高利妥昔单抗时代弥漫性大 B 细胞淋巴瘤(DLBCL)的区分和预测准确性。
我们回顾性地收集了 2005 年 1 月 1 日至 2018 年 12 月 31 日期间在中国医学科学院肿瘤医院接受基于 R-CHOP 的免疫化疗方案治疗的 873 例原发性 DLBCL 患者的治疗前数据。来自福建省肿瘤医院的 175 例 DLBCL 患者的独立队列用于外部验证。
年龄、ECOG PS、结外病灶数、Ann Arbor 分期、肿块病和 LDH 水平被筛选出来用于建立列线图和基于网络的生存率计算器。列线图在训练、内部验证和外部验证队列中的 C 指数分别为 0.761、0.758 和 0.768。基于列线图的风险分层模型有效地将患者分为三个不同的风险组。K-M 生存曲线表明,与 IPI、R-IPI 和 NCCN-IPI 相比,新的风险分层模型在训练和两个验证队列中均具有更高的预测准确性。此外,新模型(0.763)预测 5 年总生存率的曲线下面积(AUC)值高于 IPI(0.749)、R-IPI(0.725)和 NCCN-IPI(0.727)在训练队列中的值。在内部和外部验证队列中均观察到了类似的结果。
总之,我们成功开发和验证了一种新的风险分层模型和基于网络的生存率计算器,与利妥昔单抗时代的 IPI、R-IPI 和 NCCN-IPI 相比,该模型具有更高的区分和预测准确性。