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Updated: May 16, 2025
Translational Orthotopic Models of Glioblastoma Multiforme
Published on: February 17, 2023
Longitudinal analysis of radiologic progression patterns in glioblastoma: investigating prognosis using a multi-state
Hong Guo1,2, Xiaoguang Li1,2, Haipeng Tong1,2
1Department of Radiology, Daping Hospital, Army Medical University, 10# Changjiang Branch Road, Chongqing, China.
Background:
This study aimed to longitudinally investigate the evolution and prognosis of radiologic progression patterns (RPPs) in glioblastoma (GBM) using multi-state model (MSM).
Methods:
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.
Results:
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.
Conclusion:
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.
