Development and validation of a multipredictor nomogram for GBM survival prediction.

<p>(a) Multi-predictor nomogram for evaluating overall survival (OS) in GBM patients. The nomogram integrates selected radiomic features and clinical variables, allowing for individualized survival predictions. (b) Kaplan-Meier survival curves in the training cohort, stratified by risk groups...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Han Wang (254423) (author)
منشور في:	2025
الموضوعات:	Medicine Genetics Neuroscience Biotechnology Cancer Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified significant prognostic factors least absolute shrinkage improving therapeutic interventions gross total resection predict overall survival meier survival analysis clinical &# 8210 kaplan &# 8210 cox proportional hazards multiregional radiomics model preclinical gbm patients predicting risk stratification wildtype gbm patients glioblastoma </ p wildtype gbm radiomics model survival prediction p </ compare survival gbm patients radiomics models radiomic model integrated clinical clinical models xlink "> tumor microenvironment thus could three sub study aimed standalone radiomic selection operator risk score risk groups risk group retrospectively analyzed regions individually rank test radiomic signature radiomic features isocitrate dehydrogenase important tool 6 months 3 years 3 months 1 year 05 ).
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Development and validation of a multipredictor nomogram for GBM survival prediction.

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