ReviewJournal of food and drug analysis2019
Development of biomarkers of genitourinary cancer using mass spectrometry-based clinical proteomics.
Review in Journal of food and drug analysis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Volatile Organic Metabolites as Potential Biomarkers for Genitourinary Cancers: Review of the Applications and Detection Methods.Metabolites · 2025Review
- Proteomic analysis of the urothelial cancer landscape.Nature communications · 2024Article
- Emerging proteins involved in castration‑resistant prostate cancer via the AR‑dependent and AR‑independent pathways (Review).International journal of oncology · 2023Review
- Changes of Development from Childhood to Late Adulthood in Rats Tracked by Urinary Proteome.Molecular & cellular proteomics : MCP · 2023Article
- A simple urine test by 3D-plus-3D immunoassay guides preciseBioengineering & translational medicine · 2023Article
- Comparison of Magnetic Resonance Imaging-Based Radiomics Features with Nomogram for Prediction of Prostate Cancer Invasion.International journal of general medicine · 2023Article
- A glance at the emerging diagnostic biomarkers in the most prevalent genitourinary cancers.Saudi journal of biological sciences · 2022Review
- Review
- Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers.Life (Basel, Switzerland) · 2022Review
- Changes in the urinary proteome before and after quadrivalent influenza vaccine and COVID-19 vaccination.Frontiers in immunology · 2022Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate, bladder and kidney cancer are the three most common types of genitourinary cancer in the world. Of these, prostate and bladder cancers are within the top 10 most common cancers in men. Notably, kidney cancer causes no obvious symptoms in the early stages. To satisfy clinical-management requirements, researchers have developed numerous biomarkers by applying proteomic approaches using clinical serum, urine and tissue specimens, as well as cell and animal models. Through application of biomarker pipeline protocols, including discovery, verification and validation phases, and mass-spectrometric based proteomic platforms coupled with multiplexed quantification assays, these studies have led to recent rapid progress in this area. With improvements in mass-spectrometric based proteomic techniques, numerous promising biomarker candidates and marker panels for various clinical purposes have been proposed. Verification of novel protein biomarker candidates is very resource demanding (e.g. on the clinical and laboratory sides). With the support of national consortia, it is now possible to investigate the future clinical use of such biomarker strategies and assess their cost-effectiveness in personalized medicine.
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.