Determining the feasibility of calculating pancreatic cancer risk scores for people with new-onset diabetes in primary care (DEFEND PRIME): study protocol.

Introduction: Worldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis.

BMI and HbA1c are metabolic markers for pancreatic cancer: Matched case-control study using a UK primary care database.

Background: Weight loss, hyperglycaemia and diabetes are known features of pancreatic cancer. We quantified the timing and the amount of changes in body mass index (BMI) and glycated haemoglobin (HbA1c), and their association with pancreatic cancer from five years before diagnosis.

Methods: A matched case-control study was undertaken within 590 primary care practices in England, United Kingdom.

Pancreatic Cancer From the Patient Perspective: The Time to Act is Now.

Pancreatic cancer is a disease requiring urgent attention from governments and policymakers. Recently, a state of emergency has been declared for this cancer-being the fourth most common cause of cancer deaths in the European Union, it has the lowest survival rate of all common cancers. One of the major reasons pancreatic cancer is associated with such poor outcomes is because it is usually diagnosed at a late stage.

Using Primary Care Data to Report Real-World Pancreatic Cancer Survival and Symptomatology.

Pancreatic cancer is the 10th most common cancer diagnosed; despite recent advances in many areas of oncology, survival remains poor, in part owing to late diagnosis. Whilst primary care data are used widely for epidemiology and pharmacovigilance, they are less used for observing survival. In this study we extracted a pancreatic cancer cohort from a nationally representative English primary care database of electronic health records (EHRs) and reported on their symptom and mortality data.