Trial reportOncotarget2014
Diagnosis of bladder cancer and prediction of survival by urinary metabolomics.
Trial report in Oncotarget, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 2 of them syntheses 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
78 citing papers in PubMed, 2 syntheses or guidelines pooled it, 149 citations in OpenAlex.
- Metabolomics and metabolites in cancer diagnosis and treatment.Molecular biomedicine · 2025Pooled it
- Unmasking the Metabolite Signature of Bladder Cancer: A Systematic Review.International journal of molecular sciences · 2024Pooled it
- Bladder cancer recurrence surveillance by urine metabolomics analysis.Scientific reports · 2018Trial
- A systematic DoE approach for optimizing urinary LC-HRMS metabolomics: enhancing reliability in bladder cancer profiling.Analytical and bioanalytical chemistry · 2026Article
- LC-MS-Based Metabolomics and Proteomics Sample Preparation of Urine: Methods and Multi-Omics Integration.Advances in experimental medicine and biology · 2026Review
- An NMR Metabolomics Analysis Pipeline for Human Neutrophil Samples with Limited Source Material.Metabolites · 2025Article
- The role of spectral characteristics of urine in bladder cancer diagnostics.Scientific reports · 2025Article
- Multilevel plasticity and altered glycosylation drive aggressiveness in hypoxic and glucose-deprived bladder cancer cells.iScience · 2025Article
- Volatile Organic Metabolites as Potential Biomarkers for Genitourinary Cancers: Review of the Applications and Detection Methods.Metabolites · 2025Review
- Bladder cancer biomarkers.Exploration of targeted anti-tumor therapy · 2025Review
- Metabolomics for the diagnosis of bladder cancer: A systematic review.Asian journal of urology · 2024Review
- Metabolomic profiling of human bladder tissue extracts.Metabolomics : Official journal of the Metabolomic Society · 2024Article
- Untargeted urinary metabolomics for bladder cancer biomarker screening with ultrahigh-resolution mass spectrometry.Scientific reports · 2023Article
- Urinary Biomarkers and Point-of-Care Urinalysis Devices for Early Diagnosis and Management of Disease: A Review.Biomedicines · 2023Review
- Untargeted ultra-high-resolution mass spectrometry metabolomic profiling of blood serum in bladder cancer.Scientific reports · 2022Article
- Lung cancer metabolomic data from tumor core biopsies enables risk-score calculation for progression-free and overall survival.Metabolomics : Official journal of the Metabolomic Society · 2022Article
- Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer.International journal of molecular sciences · 2022Review
- MALDI-TOF/MS Analysis of Non-Invasive Human Urine and Saliva Samples for the Identification of New Cancer Biomarkers.Molecules (Basel, Switzerland) · 2022Review
- Review
- Urinary Metabolic Markers of Bladder Cancer: A Reflection of the Tumor or the Response of the Body?Metabolites · 2021Review
18 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bladder cancer (BC) is a common cancer but diagnostic modalities, such as cystoscopy and urinary cytology, have limitations. Here, high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOFMS) was used to profile urine metabolites of 138 patients with BC and 121 control subjects (69 healthy people and 52 patients with hematuria due to non-malignant diseases). Multivariate statistical analysis revealed that the cancer group could be clearly distinguished from the control groups on the basis of their metabolomic profiles, even when the hematuric control group was included. Patients with muscle-invasive BC could also be distinguished from patients with non-muscle-invasive BC on the basis of their metabolomic profiles. Successive analyses identified 12 differential metabolites that contributed to the distinction between the BC and control groups, and many of them turned out to be involved in glycolysis and betaoxidation. The association of these metabolites with cancer was corroborated by microarray results showing that carnitine transferase and pyruvate dehydrogenase complex expressions are significantly altered in cancer groups. In terms of clinical applicability, the differentiation model diagnosed BC with a sensitivity and specificity of 91.3% and 92.5%, respectively, and comparable results were obtained by receiver operating characteristic analysis (AUC = 0.937). Multivariate regression also suggested that the metabolomic profile correlates with cancer-specific survival time. The excellent performance and simplicity of this metabolomics-based approach suggests that it has the potential to augment or even replace the current modalities for BC diagnosis.
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.