Construction and application value of prediction model of pancreatic fistula after pancreaticoduodenectomy
10.3760/cma.j.cn115610-20200409-00240
- VernacularTitle:构建胰十二指肠切除术后胰瘘预测模型及其应用价值
- Author:
Xibo XU
1
;
Chengpeng JIA
;
Yong JIA
;
Hongyang LIU
;
Binru ZHANG
;
Yongwei WANG
;
Le LI
;
Hua CHEN
;
Bei SUN
Author Information
1. 哈尔滨医科大学附属第一医院胰胆外科 哈尔滨医科大学附属第一医院肝脾外科国家重点实验室 150001
- From:Chinese Journal of Digestive Surgery
2020;19(4):408-413
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a prediction model of pancreatic fistula after pancreaticoduodenectomy and explore its application value.Methods:The retrospective case-control study was conducted. The clinicopathological data of 285 patients with periampullary diseases who underwent pancreaticoduodenectomy in the the First Affiliated Hospital of Harbin Medical University from January 2015 to September 2018 were collected. There were 183 males and 102 females, aged (56±14)years, with a range from 12 to 84 years. According to the random numbers showed in the computer, patients were randomly divided into training dataset consisting of 214 patients and validation dataset consisting of 71 patients, with a ratio of 3∶1. The training dataset was used to construct prediction model, and the validation dataset was used to evaluate performance of prediction model. Observation indicators: (1) incidence of postoperative pancreatic fistula; (2) construction of prediction model of pancreatic fistula after pancreaticoduodenectomy; (3) validation of prediction model of pancreatic fistula after pancreaticoduodenectomy. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was analyzed by the t test. Measurement data with skewed distribution were represented as M (range), and comparison between groups was analyzed using the Mann-Whitney rank sum test. Count data were described as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. Univariate analysis and multivariate analysis were conducted using the Logistic regression model. The accuracy of prediction model was analyzed by drawing receiver operating characteristic curve and calculating area under curve (AUC). Results:(1) Incidence of postoperative pancreatic fistula: of 214 patients in the training dataset, 45 patients had postoperative pancreatic fistula, including 39 of grade B and 6 of grade C, respectively. (2) Construction of prediction model of pancreatic fistula after pancreaticoduodenectomy. Results of univariate analysis showed that body mass index(BMI), diameter of the main pancreatic duct on computed tomography (CT) scan, diameter of the main pancreatic duct by intraoperative exploration, pancreas texture, and level of amylase in ascites at the postoperative first day were related factors for pancreatic fistula after pancreaticoduodenectomy ( χ2=32.450, 15.789, 19.577, 4.559, Z=-7.962, P<0.05). Results of multivariate analysis showed that BMI>25 kg/m 2, diameter of the main pancreatic duct by intraoperative exploration <3 mm and level of amylase in ascites at the postoperative first day >2 651U/L were independent risk factors for pancreatic fistula after pancreaticoduodenectomy ( odds ratio=0.148, 4.286, 0.086, 95% confidence interval: 0.058-0.376, 1.736-10.580, 0.032-0.231, P<0.05). Based on results of multivariate analysis, a prediction model of pancreatic fistula after pancreaticoduodenectomy was built: the predicted value of pancreatic fistula=Exp[0.452-1.914(BMI)+ 1.455(diameter of the main pancreatic duct by intraoperative exploration)-2.451(level of amylase in ascites at the postoperative first day)]/1+ Exp[0.452-1.914(BMI)+ 1.455(diameter of the main pancreatic duct by intraoperative exploration)-2.451(level of amylase in ascites at the postoperative first day)]. The model had the AUC of 0.888 (95% confidence interval : 0.832-0.943, P<0.05). (3) Validation of prediction model of pancreatic fistula after pancreaticoduodenectomy: in the validation dataset, the prediction model of pancreatic fistula after pancreaticoduodenectomy had the AUC of 0.868 (95% confidence interval: 0.780-0.957, P<0.05). There was no significant difference in the AUC between the training dataset and validation dataset ( Z=0.514, P>0.05). Conclusions:BMI>25 kg/m 2, diameter of the main pancreatic duct by intraoperative exploration <3 mm and level of amylase in ascites at the postoperative first day >2 651 U/L are independent risk factors for pancreatic fistula after pancreaticoduodenectomy. Construction of a prediction model of pancreatic fistula after pancreaticoduo-denectomy can effectively predict the risks of postoperative pancreatic fistula.
