ArticleBritish journal of cancer2020
Development of PancRISK, a urine biomarker-based risk score for stratified screening of pancreatic cancer patients.
Article in British journal of cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04449406 (Early Detection of Pancreatic Adenocarcinoma), which is not on this map. Cited by 33 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Early Detection of Pancreatic Adenocarcinoma (PDAC) Using a Panel of Biomarkers (UroPanc)
Who cites it
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 62 citations in OpenAlex.
- Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Pooled it
- From radiomics to transformers in pancreatic cancer detection and prognosis.Frontiers in medicine · 2025Pooled it
- Review
- Incorporation of explainable artificial intelligence in ensemble machine learning-driven pancreatic cancer diagnosis.Scientific reports · 2025Article
- A novel signature predicts prognosis in pancreatic cancer based on tumor membrane-associated genes.Heliyon · 2025Article
- Construction of feature selection and efficacy prediction model for transformation therapy of locally advanced pancreatic cancer based on CT,Cancer cell international · 2025Article
- Current paradigm and futuristic vision on new-onset diabetes and pancreatic cancer research.Frontiers in pharmacology · 2025Review
- A comprehensive multi-omics analysis uncovers the associations between gut microbiota and pancreatic cancer.Frontiers in microbiology · 2025Article
- Highly accurate diagnosis of pancreatic cancer by integrative modeling using gut microbiome and exposome data.iScience · 2024Article
- Deep Learning Applications in Pancreatic Cancer.Cancers · 2024Review
- Analysis of urinary potassium isotopes and association with pancreatic health: healthy, diabetic and cancerous states.Frontiers in endocrinology · 2024Article
- RNA-seq profiling identified a three-lncRNA panel in serum as potential biomarker for muscle-invasive bladder cancer.Frontiers in oncology · 2024Article
- Evaluation of urinary C-reactive protein as an early detection biomarker for pancreatic ductal adenocarcinoma.Frontiers in oncology · 2024Article
- Exploring the application and future outlook of Artificial intelligence in pancreatic cancer.Frontiers in oncology · 2024Review
- Improving Pancreatic Cyst Management: Artificial Intelligence-Powered Prediction of Advanced Neoplasms through Endoscopic Ultrasound-Guided Confocal Endomicroscopy.Biomimetics (Basel, Switzerland) · 2023Review
- Artificial intelligence in pancreatic cancer: diagnosis, limitations, and the future prospects-a narrative review.Journal of cancer research and clinical oncology · 2023Review
- Review
- Automated classification of urine biomarkers to diagnose pancreatic cancer using 1-D convolutional neural networks.Journal of biological engineering · 2023Article
- Urine biomarkers enable pancreatic cancer detection up to 2 years before diagnosis.International journal of cancer · 2023Article
- Artificial Intelligence-The Rising Star in the Field of Gastroenterology and Hepatology.Diagnostics (Basel, Switzerland) · 2023Review
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Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
Abstract
backgroundAn accurate and simple risk prediction model that would facilitate earlier detection of pancreatic adenocarcinoma (PDAC) is not available at present. In this study, we compare different algorithms of risk prediction in order to select the best one for constructing a biomarker-based risk score, PancRISK.
methodsThree hundred and seventy-nine patients with available measurements of three urine biomarkers, (LYVE1, REG1B and TFF1) using retrospectively collected samples, as well as creatinine and age, were randomly split into training and validation sets, following stratification into cases (PDAC) and controls (healthy patients). Several machine learning algorithms were used, and their performance characteristics were compared. The latter included AUC (area under ROC curve) and sensitivity at clinically relevant specificity.
resultsNone of the algorithms significantly outperformed all others. A logistic regression model, the easiest to interpret, was incorporated into a PancRISK score and subsequently evaluated on the whole data set. The PancRISK performance could be even further improved when CA19-9, commonly used PDAC biomarker, is added to the model.
conclusionPancRISK score enables easy interpretation of the biomarker panel data and is currently being tested to confirm that it can be used for stratification of patients at risk of developing pancreatic cancer completely non-invasively, using urine samples.
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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.