期刊
HEPATOBILIARY SURGERY AND NUTRITION
卷 8, 期 3, 页码 211-218出版社
AME PUBL CO
DOI: 10.21037/hbsn.2019.03.17
关键词
Pancreatic fistula; pancreatoduodenectomy (PD); predictive score
资金
- Korea Health Industry Development Institute (KHIDI) - Ministry of Health & Welfare, Republic of Korea [HI16C2037]
- Collaborative Genome Program for Fostering New Post-Genome Industry of the National Research Foundation - Ministry of Science and ICT [NRF-2017M3C9A5031591]
Background: Although several prediction models for the occurrence of postoperative pancreatic fistula (POPF) after pancreatoduodenectomy (PD) exist, all were established using Western cohorts. Large-scale external validation studies in Eastern cohorts that consider demographic variables including lower body mass index (BMI) are scarce. The purpose of this study was to externally validate POPF prediction models using nationwide large-scale Korean cohorts. Methods: Nine tertiary university hospitals in the Republic of Korea participated. Patients' preoperative characteristics, intraoperative factors, and pathologic findings were evaluated. POPF grades were determined according to the 2016 International Study Group on Pancreatic Surgery definition. Three POPF risk models (Callery, Roberts, and Mungroop) were selected for external validation. Results: A total of 1,898 PD patients were enrolled. A non-pancreatic disease diagnosis [hazard ratio (HR), 1.856; 95% confidence interval (CI), 1.223-2.817; P=0.004), higher preoperative BMI (HR, 1.069; 95% CI, 1.019-1.121; P=0.006), and soft pancreatic texture (HR, 1.859; 95% CI, 1.264-2.735; P=0.002) were independent risk factors for clinically relevant POPF (CR-POPF). The area under the receiver operating characteristic curve (AUC) values were 0.61, 0.64, and 0.63 on the Callery, Roberts, and Mungroop models, respectively; all were lower than those published in each external validation study. Conclusions: Western POPF prediction models performed less well when applied to Korean cohorts. Thus, a large-scale Eastern-specific and externally validated POPF prediction model is needed.
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