ArticleNeuro-oncology2017
Leveraging molecular datasets for biomarker-based clinical trial design in glioblastoma.
Article in Neuro-oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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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.
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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.
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Who cites it
19 citing papers in PubMed, 27 citations in OpenAlex.
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- VAL-083 is effective in patients with newly-diagnosed MGMT-unmethylated glioblastoma: report of phase II study.Discover oncology · 2025Article
- Serum p-Cresol and 7-HOCA Levels and Fatty Acid and Purine Metabolism Are Associated with Survival, Progression, and Molecular Classification in GB-Serum Proteome and Metabolome Analysis Pre vs. Post Up-Front Chemoirradiation.Current oncology (Toronto, Ont.) · 2025Article
- Validation of Predictive Analyses for Interim Decisions in Clinical Trials.JCO precision oncology · 2023Review
- Cost Matrix of Molecular Pathology in Glioma-Towards AI-Driven Rational Molecular Testing and Precision Care for the Future.Biomedicines · 2022Review
- The Next Frontier in Health Disparities-A Closer Look at Exploring Sex Differences in Glioma Data and Omics Analysis, from Bench to Bedside and Back.Biomolecules · 2022Review
- Sp1 induced gene TIMP1 is related to immune cell infiltration in glioblastoma.Scientific reports · 2022Article
- CircCDC45 promotes the malignant progression of glioblastoma by modulating the miR-485-5p/CSF-1 axis.BMC cancer · 2021Article
- Preoperative Magnetic Resonance Imaging Radiomics for Predicting Early Recurrence of Glioblastoma.Frontiers in oncology · 2021Article
- How far will the VoyagerCNS oncology · 2019Article
- A platform for efficient early evaluation of biomarker-associated therapies in newly diagnosed IDH wild-type, MGMT unmethylated glioblastoma.Neuro-oncology · 2019Article
- Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT): A Bayesian Adaptive Platform Trial to Develop Precision Medicines for Patients With Glioblastoma.JCO precision oncology · 2019Article
- Copy number profiling across glioblastoma populations has implications for clinical trial design.Neuro-oncology · 2018Article
- The FDA NIH Biomarkers, EndpointS, and other Tools (BEST) resource in neuro-oncology.Neuro-oncology · 2018Review
- Platform trials arrive on time for glioblastoma.Neuro-oncology · 2018Article
- Toward more informative biomarker-based clinical trials in glioblastoma.Neuro-oncology · 2017Article
- Evaluating hematologic parameters in newly diagnosed and recurrent glioblastoma: Prognostic utility and clinical trial implications of myelosuppression.Neuro-oncology advancesArticle
- Implementing targeted therapies in the treatment of glioblastoma: Previous shortcomings, future promises, and a multimodal strategy recommendation.Neuro-oncology advancesReview
- Association of plasma cell-free DNA with survival in patients with IDH wild-type glioblastoma.Neuro-oncology advancesArticle
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundBiomarkers can improve clinical trial efficiency, but designing and interpreting biomarker-driven trials require knowledge of relationships among biomarkers, clinical covariates, and endpoints. We investigated these relationships across genomic subgroups of glioblastoma (GBM) within our institution (DF/BWCC), validated results in The Cancer Genome Atlas (TCGA), and demonstrated potential impacts on clinical trial design and interpretation.
methodsWe identified genotyped patients at DF/BWCC, and clinical associations across 4 common GBM genomic biomarker groups were compared along with overall survival (OS), progression-free survival (PFS), and survival post-progression (SPP). Significant associations were validated in TCGA. Biomarker-based clinical trials were simulated using various assumptions.
resultsEpidermal growth factor receptor (EGFR)(+) and p53(-) subgroups were more likely isocitrate dehydrogenase (IDH) wild-type. Phosphatidylinositol-3 kinase (PI3K)(+) patients were older, and patients with O6-DNA methylguanine-methyltransferase (MGMT)-promoter methylation were more often female. OS, PFS, and SPP were all longer for IDH mutant and MGMT methylated patients, but there was no independent prognostic value for other genomic subgroups. PI3K(+) patients had shorter PFS among IDH wild-type tumors, however, and no DF/BWCC long-term survivors were either EGFR(+) (0% vs 7%, P = .014) or p53(-) (0% vs 10%, P = .005). The degree of biomarker overlap impacted the efficiency of Bayesian-adaptive clinical trials, while PFS and OS distribution variation had less impact. Biomarker frequency was proportionally associated with sample size in all designs.
conclusionsWe identified several associations between GBM genomic subgroups and clinical or molecular prognostic covariates and validated known prognostic factors in all survival periods. These results are important for biomarker-based trial design and interpretation of biomarker-only and nonrandomized trials.
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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.