In 403 patients suspected of having pancreatic cancer, we prospectively studied a combination assay of various serum tumor markers: CA19-9, DUPAN2, tissue polypeptide antigen, elastase 1, gamma-glutamyltranspeptidase, lactate dehydrogenase, lipase, amylase, and alkaline phosphatase. The diagnostic value of each marker was compared with a multivariate analysis (computer-aided multivariate and pattern analysis system for pancreatic cancer examine-1: CAMPAS-PX1). Pancreatic cancer was subsequently identified in 47 patients. CAMPAS-PX1 had higher negative in health and positive predictability than those of each marker used alone in the diagnosis of pancreatic cancer. CAMPAS-PX1 proved the most effective marker for diagnosing pancreatic cancer, but in terms of its cost/benefit ration CAMPAS-PX1 was not superior to CA19-9 used alone. In this prospective trial, we experienced poor generalizability in the statistical models (CAMPAS-PX1). We believe that selection bias was present in samples used for model building. Based on this study a new model has been designed.
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http://dx.doi.org/10.1097/00006676-199411000-00009 | DOI Listing |
Ann Surg Oncol
January 2025
Hepato-Pancreato-Biliary Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Discov Oncol
January 2025
Department of Laboratory, the Second Hospital of Shanxi Medical University, No. 382, Wuyi Road, Taiyuan, 030001, Shanxi, People's Republic of China.
Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.
Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.
mSphere
January 2025
State Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ningning Liu works in the field of fungal infection and cancer progression, with a particular focus on the mechanism of host-pathogen interaction. In this mSphere of influence article, he reflects on how papers entitled "The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL," by B. Aykut, S.
View Article and Find Full Text PDFJ Hepatobiliary Pancreat Sci
January 2025
Department of Gastroenterology, Shizuoka General Hospital, Shizuoka, Japan.
Cureus
January 2025
Hepato-Pancreato-Biliary (HPB) Unit, University Hospital Southampton NHS Foundation Trust, Southampton, GBR.
Background The relationship between physical activity and incident pancreatic cancer is poorly defined, and the evidence to date is inconsistent, largely due to small sample sizes and insufficient incident outcomes. Using the UK Biobank cohort dataset, the association between physical activity levels at recruitment and incident pancreatic ductal adenocarcinoma (PDAC) at follow-up was analysed. Method Physical activity, the key exposure, was quantified using Metabolic Equivalent Task (MET) values and categorised into walking, moderate, and vigorous activity.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!