Talk to the Veterans Crisis Line now
U.S. flag
An official website of the United States government

VA Health Systems Research

Go to the VA ORD website
Go to the QUERI website

HSR&D Citation Abstract

Search | Search by Center | Search by Source | Keywords in Title

A clinical prediction model to assess risk for pancreatic cancer among patients with prediabetes.

Boursi B, Finkelman B, Giantonio BJ, Haynes K, Rustgi AK, Rhim AD, Mamtani R, Yang YX. A clinical prediction model to assess risk for pancreatic cancer among patients with prediabetes. European journal of gastroenterology & hepatology. 2022 Jan 1; 34(1):33-38.

Dimensions for VA is a web-based tool available to VA staff that enables detailed searches of published research and research projects.

If you have VA-Intranet access, click here for more information vaww.hsrd.research.va.gov/dimensions/

VA staff not currently on the VA network can access Dimensions by registering for an account using their VA email address.
   Search Dimensions for VA for this citation
* Don't have VA-internal network access or a VA email address? Try searching the free-to-the-public version of Dimensions



Abstract:

BACKGROUND: Early detection of pancreatic ductal adenocarcinoma (PDA) may improve survival. We previously developed a clinical prediction model among patients with new-onset diabetes to help identify PDAs 6?months prior to the clinical diagnosis of the cancer. We developed and internally validated a new model to predict PDA risk among those newly diagnosed with impaired fasting glucose (IFG). METHODS: We conducted a retrospective cohort study in The Health Improvement Network (THIN) (1995-2013) from the UK. Eligible study patients had newly diagnosed IFG during follow-up in THIN. The outcome was incident PDA diagnosed within 3?years of IFG diagnosis. Candidate predictors were factors associated with PDA, glucose metabolism or both. RESULTS: Among the 138?232 eligible patients with initial IFG diagnosis, 245 (0.2%) were diagnosed with PDA within 3?years. The median time from IFG diagnosis to clinical PDA diagnosis was 326?days (IQR 120-588). The final prediction model included age, BMI, proton pump inhibitor use, total cholesterol, low-density lipoprotein, alanine aminotransferase and alkaline phosphatase. The model achieved good discrimination [area under the curve 0.71 (95% CI, 0.67-0.75)] and calibration (Hosmer and Lemeshow goodness-of-fit test P? > 0.05 in 17 of the 20 imputed data sets) with optimism of 0.0012662 (95% CI, -0.00932 to 0.0108771). CONCLUSIONS: We developed and internally validated a sequential PDA prediction model based on clinical information routinely available at the initial appearance of IFG. If externally validated, this model could significantly extend our ability to detect PDAs at an earlier stage.





Questions about the HSR website? Email the Web Team

Any health information on this website is strictly for informational purposes and is not intended as medical advice. It should not be used to diagnose or treat any condition.