ArticleBMC surgery2021
A nomogram for individualized prediction of overall survival in patients with newly diagnosed glioblastoma: a real-world retrospective cohort study.
Article in BMC surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Pre-Clinical Systems Using Artificial Microenvironments and Anti-Migratory Drugs to Control Migration of Glioblastoma Cells.Expert reviews in molecular medicine · 2025Pooled it
- Biology-informed risk stratification of glioblastoma by integrating MRI-based intratumoral heterogeneity with clinical features: a multicenter validation study.Experimental hematology & oncology · 2026Article
- Glioblastoma treatment patterns and outcomes over 18 years in an Irish cancer centre.Irish journal of medical science · 2026Article
- A Language Performance Model for Predicting Glioma Recurrence and Molecular Biomarkers: A Retrospective Cohort Study.Brain and behavior · 2026Article
- Nomograms for predicting survival of elderly patients with newly diagnosed glioblastoma: a secondary analysis of the CCTG CE.6 trial.Journal of neuro-oncology · 2026Article
- Algorithm-based analysis of lymph node dissection strategies and survival outcomes in primary oral squamous cell carcinoma.Frontiers in oncology · 2025Article
- Risk factors and a new nomogram for glioblastoma: based on a retrospective study.Frontiers in immunology · 2025Article
- Prediction of prognosis in glioblastoma with radiomics features extracted by synthetic MRI images using cycle-consistent GAN.Physical and engineering sciences in medicine · 2024Article
- Article
- Review
- Bioenergetic Profiling in Glioblastoma Multiforme Patients with Different Clinical Outcomes.Metabolites · 2023Article
- A 3-miRNA Signature Enables Risk Stratification in Glioblastoma Multiforme Patients with Different Clinical Outcomes.Current oncology (Toronto, Ont.) · 2022Article
- Potential of NovelFrontiers in pharmacology · 2022Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aimed to identify the most valuable predictors of prognosis in glioblastoma (GBM) patients and develop and validate a nomogram to estimate individualized survival probability.
methodsWe conducted a real-world retrospective cohort study of 987 GBM patients diagnosed between September 2010 and December 2018. Computer generated random numbers were used to assign patients into a training cohort (694 patients) and internal validation cohort (293 patients). A least absolute shrinkage and selection operator (LASSO)-Cox model was used to select candidate variables for the prediction model. Cox proportional hazards regression was used to estimate overall survival. Models were internally validated using the bootstrap method and generated individualized predicted survival probabilities at 6, 12, and 24 months, which were compared with actual survival.
resultsThe final nomogram was developed using the Cox proportional hazards model, which was the model with best fit and calibration. Gender, age at surgery, extent of tumor resection, radiotherapy, chemotherapy, and IDH1 mutation status were used as variables. The concordance indices for 6-, 12-, 18-, and 24-month survival probabilities were 0.776, 0.677, 0.643, and 0.629 in the training set, and 0.725, 0.695, 0.652, and 0.634 in the validation set, respectively.
conclusionsOur nomogram that assesses individualized survival probabilities (6-, 12-, and 24-month) in newly diagnosed GBM patients can assist healthcare providers in optimizing treatment and counseling patients.
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