ReviewCureus2024
Metabolite Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: A Systematic Review.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Long-Term Weight Regain Outcome Post-Bariatric Surgery: Key Influencing Factors.Obesity surgery · 2026Article
- Detection of Pancreatic Cancer via Specific Metabolite Markers: A Metabolomics Approach.Health science reports · 2026Article
- Machine learning-based multimodal biomarkers enable accurate diagnosis and early detection of pancreatic ductal adenocarcinoma.Scientific reports · 2026Article
- Pancreatic Cancer Screening in Patients with Type 2 Diabetes Mellitus: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Robotic 3-arm Roux-en-Y gastric bypass: a feasible, safe and cost-effective approach based on patient selection.Journal of robotic surgery · 2025Article
- Identification of Anticancer Target Combinations to Treat Pancreatic Cancer and Its Associated Cachexia Using Constraint-Based Modeling.Molecules (Basel, Switzerland) · 2025Article
- Updates in the diagnosis and management of ductal adenocarcinoma of the pancreas.World journal of clinical oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a poor prognosis. This poor prognosis is largely attributed to a late-stage diagnosis. Recent advancements in metabolomics have emerged as a promising avenue for biomarker discovery in PDAC. This systematic review evaluates the potential of metabolite biomarkers for early detection of PDAC. Four studies meeting the inclusion criteria were analyzed, encompassing experimental, case-control, and prospective cohort designs. Key findings include the identification of distinct metabolic subtypes in PDAC with varying sensitivities to metabolic inhibitors. A biomarker signature comprising nine metabolites plus CA19-9 showed high accuracy in distinguishing PDAC from chronic pancreatitis, outperforming CA19-9 alone. Another study identified a five-metabolite signature demonstrating high diagnostic accuracy for pancreatic cancer, differentiating it from type 2 diabetes mellitus. A two-metabolite model (isoleucine and adrenic acid) showed superior performance in detecting stage-I PDAC compared to CA19-9. These studies consistently demonstrate altered metabolic pathways in PDAC patients compared to healthy controls and those with benign pancreatic conditions. Integrating metabolomic data with other molecular profiling approaches has become a powerful strategy for improving diagnostic accuracy. However, challenges remain, including the influence of confounding factors, the need for large-scale validation studies, and the standardization of metabolomic methods. The potential of artificial intelligence in interpreting complex metabolomic data offers promising avenues for future research. This review highlights the significant potential of metabolite biomarkers in early PDAC detection while emphasizing the need for further validation and refinement of these approaches.
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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.