ArticleCancers2020
Identification of Pre-Diagnostic Metabolic Patterns for Glioma Using Subset Analysis of Matched Repeated Time Points.
Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Metabolomics and metabolites in cancer diagnosis and treatment.Molecular biomedicine · 2025Pooled it
- The use of blood test trends in cancer detection: a scoping review.Diagnostic and prognostic research · 2026Review
- Oncometabolites in Cancer Metabolism: Mechanistic Insights and Biomarker Potential- A Narrative Review.Health science reports · 2026Article
- Exploring metabolic signatures in urine using NMR for improved prognosis of gliomas.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Glioblastoma metabolomics: uncovering biomarkers for diagnosis, prognosis and targeted therapy.Journal of experimental & clinical cancer research : CR · 2025Review
- Towards non-invasive diagnosis of glioblastoma: identifying metabolic biomarkers in liquid biopsies using a ROC-based approach.Discover oncology · 2025Article
- Amino acid metabolism in glioblastoma pathogenesis, immune evasion, and treatment resistance.Cancer cell international · 2025Review
- Blood based metabolic markers of glioma from pre-diagnosis to surgery.Scientific reports · 2024Article
- The Association between Blood Test Trends and Undiagnosed Cancer: A Systematic Review and Critical Appraisal.Cancers · 2024Review
- Modifications of Blood Molecular Components after Treatment with Low Ozone Concentrations.International journal of molecular sciences · 2023Article
- Article
- Alterations of plasma exosomal proteins and motabolies are associated with the progression of castration-resistant prostate cancer.Journal of translational medicine · 2023Article
- Pre-diagnostic blood biomarkers for adult glioma.Frontiers in oncology · 2023Review
- Prediagnostic biomarkers for early detection of glioma-using case-control studies from cohorts as study approach.Neuro-oncology advances · 2022Article
- Distinct metabolic hallmarks of WHO classified adult glioma subtypes.Neuro-oncology · 2022Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Here, we present a strategy for early molecular marker pattern detection-Subset analysis of Matched Repeated Time points (SMART)-used in a mass-spectrometry-based metabolomics study of repeated blood samples from future glioma patients and their matched controls. The outcome from SMART is a predictive time span when disease-related changes are detectable, defined by time to diagnosis and time between longitudinal sampling, and visualization of molecular marker patterns related to future disease. For glioma, we detect significant changes in metabolite levels as early as eight years before diagnosis, with longitudinal follow up within seven years. Elevated blood plasma levels of myo-inositol, cysteine, N-acetylglucosamine, creatinine, glycine, proline, erythronic-, 4-hydroxyphenylacetic-, uric-, and aceturic acid were particularly evident in glioma cases. We use data simulation to ensure non-random events and a separate data set for biomarker validation. The latent biomarker, consisting of 15 interlinked and significantly altered metabolites, shows a strong correlation to oxidative metabolism, glutathione biosynthesis and monosaccharide metabolism, linked to known early events in tumor development. This study highlights the benefits of progression pattern analysis and provide a tool for the discovery of early markers of disease.
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.