The Investigation of the Correlation between 4 Urine Biomarkers and Intelligent Diagnosis of PDAC

Pancreatic ductal adenocarcinoma (PDAC)'s low survival rate has long been a world unsolved problem. Many past studies in recent decades proved the possibility in detecting such disease in its early stages, using new screening panel with several urinary biomarkers. However, limited studies truly focused on statistical correlation between the fluctuation of urinary biomarker concentrations and PDAC diagnosis status. We investigate the hypothesis that possible correlation between value of biomarker concentration in urinary sample and PDAC confirmed cases can be used for early diagnosis of PDAC patients. To evaluate the associations of 4 urine biomarkers and PDAC, and to predict whether this patient has pancreatic problems and determine whether he has pancreatic cancer at an early stage. The data which originally derived from an open access paper was obtained from Kaggle based on the relevance of measurements of different biomarkers to our investigation. We estimated odds ratios (ORs) and 95% CIs us in a multinomial logistic regression model. From analysis of p-value, LYVE1, REG1B and TFF1 are all possible biomarkers to indicate pateints' PDAC status. A multinomial logistic regression was made to show the correlation between selected biomarkers and diagnosis. Our study suggested that a possible real correlation exist between urinary biomarkers' concentration and PDAC diagnosis status. Our model could be used to detect patients in their early disease stages in some degrees.