ArticleCancers2023
Mass Spectrometry-Based Biomarkers to Detect Prostate Cancer: A Multicentric Study Based on Non-Invasive Urine Collection without Prior Digital Rectal Examination.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Support Vector Machine Models for Cancer Detection and Related Clinical Applications Using Omics and Omics-Adjacent Data: A Systematic Review.BioMed research international · 2026Pooled it
- Recent Developments and Applications of Capillary and Microchip Electrophoresis in Proteomics and Peptidomics (2023-2025).Journal of separation science · 2026Review
- Artificial intelligence in the early diagnosis of prostate cancer: from multimodal imaging to liquid biopsy.Frontiers in oncology · 2026Review
- In Search of Ideal Solutions for Cancer Diagnosis: From Conventional Methods to Protein Biomarkers in Liquid Biopsy.Proteomes · 2025Review
- Transforming Cancer Diagnostics: The Emergence of Liquid Biopsy and Epigenetic Markers.MedComm · 2025Review
- Article
- Unraveling molecular characteristics and tumor microenvironment dynamics of neuroendocrine prostate cancer.Journal of cancer research and clinical oncology · 2024Review
- Promoter hypermethylation of Y-chromosome geneEpigenomics · 2024Article
- Article
- The Molecular Biology of Prostate Cancer Stem Cells: From the Past to the Future.International journal of molecular sciences · 2023Review
- Pathophysiology and potential treatment modalities in women with recurrent urinary tract infection.Tzu chi medical journalReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 5 countries.
Funding
Abstract
(1) Background: Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Wide application of prostate specific antigen test has historically led to over-treatment, starting from excessive biopsies. Risk calculators based on molecular and clinical variables can be of value to determine the risk of PCa and as such, reduce unnecessary and invasive biopsies. Urinary molecular studies have been mostly focusing on sampling after initial intervention (digital rectal examination and/or prostate massage). (2) Methods: Building on previous proteomics studies, in this manuscript, we aimed at developing a biomarker model for PCa detection based on urine sampling without prior intervention. Capillary electrophoresis coupled to mass spectrometry was applied to acquire proteomics profiles from 970 patients from two different clinical centers. (3) Results: A case-control comparison was performed in a training set of 413 patients and 181 significant peptides were subsequently combined by a support vector machine algorithm. Independent validation was initially performed in 272 negative for PCa and 138 biopsy-confirmed PCa, resulting in an AUC of 0.81, outperforming current standards, while a second validation phase included 147 PCa patients. (4) Conclusions: This multi-dimensional biomarker model holds promise to improve the current diagnosis of PCa, by guiding invasive biopsies.
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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.