TY - JOUR
T1 - A clinical prediction model to assess risk for pancreatic cancer among patients with prediabetes
AU - Boursi, Ben
AU - Finkelman, Brian
AU - Giantonio, Bruce J.
AU - Haynes, Kevin
AU - Rustgi, Anil K.
AU - Rhim, Andrew D.
AU - Mamtani, Ronac
AU - Yang, Yu Xiao
N1 - Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85107201011&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107201011&partnerID=8YFLogxK
U2 - 10.1097/MEG.0000000000002052
DO - 10.1097/MEG.0000000000002052
M3 - Article
C2 - 33470698
AN - SCOPUS:85107201011
SN - 0954-691X
VL - 34
SP - 33
EP - 38
JO - European Journal of Gastroenterology and Hepatology
JF - European Journal of Gastroenterology and Hepatology
IS - 1
ER -