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DIPLOMA Approach for Standardized Pathology Assessment of Distal Pancreatectomy Specimens
Published on: February 1, 2020
Circulating inflammatory indices refine prognostic stratification and complication risk in pancreatic cancer
Jiayue Zou1,2, Yizhang Zhu2, Daobin Wang2
1Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Background:
Systemic inflammatory biomarkers offer accessible and dynamic prognostic information in pancreatic ductal adenocarcinoma (PDAC). This study explores how circulating inflammatory indices enhance risk stratification and outcome prediction for PDAC patients undergoing radical resection.
Methods:
We analyzed 368 PDAC patients categorized by clinically relevant postoperative pancreatic fistula, resectability status, and Clavien-Dindo complication scores. Blood-based inflammatory indices were used to establish clinical risk profiles. Optimal cutoff values were determined using Youden's index. A prognostic nomogram was developed through multivariable regression and the least absolute shrinkage and selection operator (LASSO) regression analysis, and its predictive performance was evaluated using time-dependent receiver operating characteristic (ROC) curves against conventional staging systems.
Results:
Patients with borderline resectable (BR) PDAC and those with severe postoperative complications showed significantly elevated inflammatory indices. Those with inflammatory markers above optimal cutoff points had significantly poorer survival. A nomogram incorporating C-reactive protein (CRP), cancer antigen 199 (CA19-9) >500 U/mL, radiological resectability, and tumor size demonstrated superior prognostic accuracy over traditional staging systems and improved clinical decision-making.
Conclusions:
Circulating inflammatory biomarkers significantly improve prognostic assessment in patients with PDAC and can reflect the risk of surgical complications. Our findings support incorporating accessible blood-based inflammatory indices into multimodal risk stratification frameworks to guide personalized treatment strategies.
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