Exploring and validating the clinical risk factors for pancreatic cancer in chronic pancreatitis patients using electronic medical records datasets: Three cohorts comprising 2,960 patients

6Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

Abstract

Background: Patients with chronic pancreatitis (CP) have an increased risk of developing pancreatic cancer (PC). The purpose of this study was to identify predictors of PC in CP patients. Methods: Electronic medical records (EMRs) of CP patients from two cohorts were collected, and a logistic regression analysis was performed to investigate the risk factors for PC. Subsequently, we validated the value of the risk prediction model with the EMRs of a third cohort. Results: The derivation cohort consisted of 2,545 CP patients, and among them, 14 patients developed PC 7 years after CP diagnosis. Cyst of the pancreas [COP; odds ratio (OR): 4.37, 95% confidence interval (CI): 1.11 to 18.40, P=0.033], loss of weight (LW; OR: 3.21, 95% CI: 0.76 to 12.91, P=0.096) and high platelet (PLT) count (OR: 1.01 per 1 increment, 95% CI: 1.00 to 1.01, P=0.042) were independent risk factors for PC among CP patients. A risk prediction equation was constructed as follows: Ln[p/(1-p)] =-6.68 + 1.55COP + 1.23LW + 0.0046PLT. The areas under the receiver operating characteristic (ROC) curve of our risk score were 0.83 and 0.72 in the derivation and validation cohorts, respectively. A score >0.0128 and >0.0122 had the best balance between sensitivity and specificity in the derivation and validation cohorts, respectively. Conclusions: In CP patients, LW, COP and high PLT count were identified as novel predictors of PC. A risk prediction model based on these factors exhibited moderate predictive value for CP patients.

Cite

CITATION STYLE

APA

Zhao, X., Lang, R., Zhang, Z., Zhao, W., Ji, Z., Tan, H., & Zhou, X. (2020). Exploring and validating the clinical risk factors for pancreatic cancer in chronic pancreatitis patients using electronic medical records datasets: Three cohorts comprising 2,960 patients. Translational Cancer Research, 9(2), 629–638. https://doi.org/10.21037/tcr.2019.11.49

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free