ArticleExperimental hematology & oncology2026
Biology-informed risk stratification of glioblastoma by integrating MRI-based intratumoral heterogeneity with clinical features: a multicenter validation study.
Article in Experimental hematology & oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
backgroundRefined risk stratification before randomization is clinically important for reducing prognostic imbalance across study arms when evaluating novel therapies for glioblastoma. However, current artificial intelligence-assisted prognostic models are often limited by complex computational pipelines, limited bedside applicability, and insufficient biological interpretability. This study aimed to develop a prognostic model, supported by an online-accessible platform, for individualized risk stratification of glioblastoma using MRI-based intratumoral heterogeneity and routinely available clinical features, and to investigate the biological meaning of model-driven risk stratification.
methodsThis retrospective multicenter study included 836 patients with isocitrate dehydrogenase-wildtype glioblastoma from six centers between October 1996 and May 2025. The habitat risk score (HRS) for each patient was derived from a proposed intratumoral heterogeneity index and quantitative metrics extracted from three-dimensional preoperative MRI-based vascular habitat mappings. Independent predictors of overall survival (OS) were identified using Cox proportional hazards regression analysis, and three prognostic models (HRS model, clinical model, and radio-clinical model) were developed and validated in spatial and temporal external sets. Model interpretability was assessed using time-stratified Shapley additive explanations (SHAP) analysis. A web-based interactive platform was implemented for rapid individualized risk assessment. The biological meaning of model-driven risk stratification was explored using transcriptomic and histologic profiling.
resultsHRS, Karnofsky performance status (KPS), O
conclusionsThis study establishes an interpretable and clinically deployable framework for glioblastoma risk stratification by integrating imaging-derived intratumoral heterogeneity with routine clinical features, without requiring complex computational infrastructure. The model also provides biologically grounded insights into model-driven risk stratification.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.