Mi Lan, Deng Jili, Qin Jiayue, Zhang Chen, Liu Lixia, Yang Shunli, Chen Libin, Wu Hua-Jun, Wang Haojie, Zhu Jun, Chen Hong, Lou Feng, Cao Shanbo, Song Yuqin, Liu Weiping
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education) Department of Lymphoma Peking University Cancer Hospital & Institute Beijing China.
Department of Medical Oncology Sichuan Clinical Research Center for Cancer Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China Chengdu China.
MedComm (2020). 2025 Jun 16;6(7):e70190. doi: 10.1002/mco2.70190. eCollection 2025 Jul.
Molecular subtyping in diffuse large B-cell lymphoma (DLBCL) leads to facilitating drug selection. However, an integrated prognostic model based on molecular subtyping and clinical features has not been well established. Here, we retrospectively performed whole genome sequencing, whole exome sequencing, and fluorescence in situ hybridization in newly diagnosed DLBCLs, established a simplified LymphType algorithm for classification evaluation, and proposed a new integrated prognostic stratification system, combined molecular subtypes and International Prognostic Index (IPI) scoring system in our in-house sequencing cohort ( = 100), and validated in three public cohorts ( = 1480). Compared with IPI scoring system and classification algorithm model alone, the discrimination ability of prognostic model based on the new integrated model showed best discrimination of overall survival with concordance index value (0.773 vs. 0.724 vs. 0.648). We subsequently established a four-category risk model defined for the integrated prognostic model as follows: low, low-intermediate, high-intermediate, and high risk, demonstrating stronger prognostic separation across all end points (all < 0.001) in our in-house cohort and three validation cohorts. Collectively, the new feasible integrated prognostic stratification system contributes to accurate prognosis assessment in clinical routine and provides a new basis for the follow-up treatment.
弥漫性大B细胞淋巴瘤（DLBCL）中的分子亚型有助于药物选择。然而，基于分子亚型和临床特征的综合预后模型尚未得到很好的建立。在此，我们对新诊断的DLBCL患者进行了回顾性全基因组测序、全外显子组测序和荧光原位杂交，建立了一种简化的LymphType算法用于分类评估，并提出了一种新的综合预后分层系统，将分子亚型与国际预后指数（IPI）评分系统相结合，应用于我们内部测序队列（n = 100），并在三个公共队列（n = 1480）中进行了验证。与单独的IPI评分系统和分类算法模型相比，基于新综合模型的预后模型对总生存期的判别能力最佳，一致性指数值分别为0.773、0.724和0.648。随后，我们为综合预后模型建立了一个四类风险模型，即低风险、低中风险、高中风险和高风险，在我们的内部队列和三个验证队列中，所有终点的预后分离能力更强（所有P < 0.001）。总体而言，新的可行的综合预后分层系统有助于临床常规中的准确预后评估，并为后续治疗提供了新的依据。
