| Title: | Identification of risk factors and construction of early-diagnosis model for predicting the risk of pancreatic cancer in new-onset diabetes population based on UK Biobank data |
| Lead Institution: | Guangdong Provincial People's Hospital |
| Principal investigator: | Professor Rufu Chen |
Application 85224
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Aims: This research aimed to identify non-genetic (environmental, demographic, etc.) and genetic factors which correlated with the risk of pancreatic ductal adenocarcinoma (PDAC) in the population of new-onset diabetes (NODM) and then subsequently to build a prediction model in order to help identify subjects with a high likelihood of having PDAC-associated diabetes in the whole population present with NODM. Scientific rationale: PDAC is associated with a very poor prognosis with a 5-year survival rate of less than 10%, principally because PDAC frequently presents at an advanced stage (85% unresectable). A screening strategy for sporadic PDAC still has not been established; given that its cancer specific symptoms occur late, early detection thereby will require screening of asymptomatic individuals. About up to 50%-80% of PDAC patients may have impaired fasting blood glucose or impaired glucose tolerance. It has been well-known that long-term diabetes increases the risk of PDAC by 40% to 100%, while the risk of PDAC in diabetic patients with a course of ! 2years -3 years (new-onset diabetes, NODM) can tremendously increase by 2 times to 7 times; moreover, about 1% patients with NODM could develop PDAC within 2 years -3 years, and it is currently believed that a large proportion of NODM are pancreatogenous diabetes mellitus caused by PDAC. Therefore, the characteristics, both genetic and non-genetic, would be different between PDAC-associated NODM and real new-onset T2DM. Through identifying the differences between PDAC patients with NODM, type 2 NODM, and healthy people, and exploring unique risk factors associated with development of PDAC in NODM population, together with advanced algorithms, may help to establish a prediction model which can help distinguish PDAC-related NODM from new-onset common T2DM patients. Project duration: With 24 months. Public health impact: Our results may help to build a strategy for the further enrichment of high-risk cases in NODM population for cost-effective follow-up and/or detailed examination for the early diagnosis of PDAC.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 9226 | Association of genetic risk and lifestyle with pancreatic cancer and their age dependency: a large prospective cohort study in the UK Biobank | Liangtang Zeng (+4) | 2023 | BMC Medicine |
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