ArticleJournal of neuro-oncology2025
Longitudinal analysis of radiologic progression patterns in glioblastoma: investigating prognosis using a multi-state model.
Article in Journal of neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
13 authors.
Funding
Abstract
backgroundThis study aimed to longitudinally investigate the evolution and prognosis of radiologic progression patterns (RPPs) in glioblastoma (GBM) using multi-state model (MSM).
methodsA 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.
resultsSignificant 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.
conclusionRPPs could stratified treatment efficacy and prognosis in GBM, with each RPP demonstrating specific temporal risk profiles and outcomes, offering valuable insights into personalized management.
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