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. 2024 May;38(5):2622-2631.
doi: 10.1007/s00464-024-10770-6. Epub 2024 Mar 18.

Analysis of factors influencing pancreatic fistula after minimally invasive pancreaticoduodenectomy and establishment of a new prediction model for clinically relevant pancreatic fistula

Yuwen Zhu #  1 , Di Wu #  1 , Hao Yang  1 , Zekun Lu  1 , Zhiliang Wang  1 , Guangchen Zu  1 , Zheng Li  2 , Xiaowu Xu  2 , Yue Zhang  3 , Xuemin Chen  4 , Weibo Chen  5
Affiliations

Analysis of factors influencing pancreatic fistula after minimally invasive pancreaticoduodenectomy and establishment of a new prediction model for clinically relevant pancreatic fistula

Yuwen Zhu et al. Surg Endosc. 2024 May.

Abstract

Background: Postoperative pancreatic fistula (POPF) is the most prevalent complications following minimally invasive pancreaticoduodenectomy (MIPD). Only one model related to MIPD exists, and previous POPF scoring prediction methods are based on open pancreaticoduodenectomy patients. Our objectives are to determine the variables that may increase the probability of pancreatic fistula following MIPD and to develop and validate a POPF predictive risk model.

Methods: Data from 432 patients who underwent MIPD between July 2015 and May 2022 were retrospectively collected. A nomogram prediction model was created using multivariate logistic regression analysis to evaluate independent factors for POPF in patients undergoing MIPD in the modeling cohort. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) and the calibration curve were used to verify the nomogram prediction model internally and externally within the modeling cohort and the verification cohort.

Results: Multivariate logistic regression analysis showed that body mass index (BMI), albumin, triglycerides, pancreatic duct diameter, pathological diagnosis and intraoperative bleeding were independent variables for POPF. On the basis of this information, a model for the prediction of risks associated with POPF was developed. In accordance with the ROC analysis, the modeling cohort's AUC was 0.819 (95% CI 0.747-0.891), the internal validation cohort's AUC was 0.830 (95% CI 0.747-0.912), and the external validation cohort's AUC was 0.793 (95% CI 0.671-0.915). Based on the calibration curve, the estimated values of POPF have a high degree of concordance with the actual values that were measured.

Conclusions: This model for predicting the probability of pancreatic fistula following MIPD has strong predictive capacity and can provide a trustworthy predictive method for the early screening of high-risk patients with pancreatic fistula after MIPD and timely clinical intervention.

Keywords: Minimally invasive pancreaticoduodenectomy; Postoperative pancreatic fistula; Prediction model; Risk factors.

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Conflict of interest statement

Yuwen Zhu, Di Wu, Hao Yang, Zekun Lu, Zhiliang Wang, Guangchen Zu, Zheng Li, Xiaowu Xu, Yue Zhang, Xuemin Chen and Weibo Chen have no conflicts of interest to disclose.

Figures

Fig. 1
Fig. 1
Nomogram calculator in prediction for postoperative pancreatic fistula after minimally invasive pancreaticoduodenectomy
Fig. 2
Fig. 2
Receiver operating characteristic (ROC) curve of predictive model in modeling cohort (a) and validation cohort (b)
Fig. 3
Fig. 3
Calibration curves for the modeling cohort (a) and validation cohort (b)
Fig. 4
Fig. 4
Receiver operating characteristic (ROC) curve (a) and calibration curve (b) of the external validation cohort
See this image and copyright information in PMC

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