Guo Hong, Li Xiaoguang, Tong Haipeng, Fang Jingqin, Du Xuesong, Cong Chao, Guo Yu, Xie Tian, Ran Qisheng, Shi Hang, Liu Suihan, Chen Xiao, Zhang Weiguo
Department of Radiology, Daping Hospital, Army Medical University, 10# Changjiang Branch Road, Chongqing, China.
Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China.
J Neurooncol. 2025 Jul;173(3):595-607. doi: 10.1007/s11060-025-05022-z. Epub 2025 Mar 31.
This study aimed to longitudinally investigate the evolution and prognosis of radiologic progression patterns (RPPs) in glioblastoma (GBM) using multi-state model (MSM).
A retrospective analysis of 119 GBM patients with confirmed progression identified four RPPs: complete (cT1, T2-circumscribed, T2-diffuse), classic-T1, non-responder, and non-local. About 11 genes were analyzed on 69 patients. Prognostic and molecular differences among RPPs were compared. A unidirectional MSM with 6 states ("surgery", "complete", "classic-T1", "non-responder", "non-local", "death") and 14 transitions was constructed to systematically analyze the trajectories and outcomes of various progression patterns in GBM.
Significant differences in first progression-free survival and overall survival were observed among RPPs (P < 0.001), while key gene alterations showed no significant differences. In the 6 months post-surgery, cumulative risk for non-responder increased, with state probabilities peaking at 5 months (20%). Between 6 and 24 months, risks for classic-T1 and complete rose, with peak state probabilities at 10-12 months (12.7%) for classic-T1 and 16 months (8.7%) for complete. Non-local progression had a lower risk, with state probabilities peaking at 9-10 months (4.7%). The cumulative mortality risk rose rapidly after progression, sequentially associated with non-local, non-responder, classic-T1, and complete. Classic-T1 progression linked to non-rim enhancement, non-response to age and subtotal resection or absence of radiotherapy, and non-local to male and multiple lesions at diagnosis.
RPPs could stratified treatment efficacy and prognosis in GBM, with each RPP demonstrating specific temporal risk profiles and outcomes, offering valuable insights into personalized management.
本研究旨在使用多状态模型(MSM)纵向研究胶质母细胞瘤(GBM)中放射学进展模式(RPPs)的演变和预后。
对119例确诊进展的GBM患者进行回顾性分析,确定了四种RPPs:完全型(cT1、T2局限型、T2弥漫型)、经典T1型、无反应型和非局灶型。对69例患者分析了约11个基因。比较了RPPs之间的预后和分子差异。构建了一个具有6个状态(“手术”、“完全型”、“经典T1型”、“无反应型”、“非局灶型”、“死亡”)和14种转变的单向MSM,以系统分析GBM中各种进展模式的轨迹和结果。
RPPs之间在首次无进展生存期和总生存期方面存在显著差异(P < 0.001),而关键基因改变无显著差异。术后6个月内无反应型的累积风险增加,状态概率在5个月时达到峰值(20%)。在6至24个月之间,经典T1型和完全型的风险增加,经典T1型的状态概率峰值在10至12个月(12.7%),完全型在16个月(8.7%)。非局灶性进展风险较低,状态概率在9至10个月时达到峰值(4.7%)。进展后累积死亡风险迅速上升,依次与非局灶型、无反应型、经典T1型和完全型相关。经典T1型进展与非边缘强化、对年龄无反应、次全切除或未接受放疗有关,非局灶型与男性及诊断时多发病灶有关。
RPPs可对GBM的治疗疗效和预后进行分层,每种RPP都显示出特定的时间风险特征和结果,为个性化管理提供了有价值的见解。