Literature DB >> 32901325

Development and Validation of a New Nomogram for Predicting Clinically Relevant Postoperative Pancreatic Fistula After Pancreatoduodenectomy.

Xi-Tai Huang1, Chen-Song Huang1, Chen Liu2,3,4, Wei Chen1, Jian-Peng Cai1, He Cheng2,3,4, Xing-Xing Jiang5, Li-Jian Liang1, Xian-Jun Yu6,7,8, Xiao-Yu Yin9.   

Abstract

BACKGROUND: There lacks an ideal model for accurately predicting clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreatoduodenectomy (PD). This study aimed at developing a nomogram with high accuracy in predicting CR-POPF after PD.
METHODS: A total of 1182 patients undergoing PD in the First Affiliated Hospital of Sun Yat-sen University (FAHSYSU, n = 762) and Fudan University Shanghai Cancer Center (FUSCC, n = 420) between January 2010 and May 2018 were enrolled. The patients from FAHSYSU were assigned as testing cohort, and those from FUSCC were used as external validation cohort. Univariate and multivariate logistic regression analyses were performed to determine the predictive factors for CR-POPF. Nomogram was developed on the basis of significant predictors. The performance of nomogram was evaluated by area under receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis.
RESULTS: In testing cohort, 87 out of 762 patients developed CR-POPF. Three predictors were significantly associated with CR-POPF, including body mass index ≥24.0 kg/m2, pancreatic duct diameter <3 mm, and drainage fluid amylase on postoperative day 1 ≥2484 units/L (all p ≤ 0.001). Prediction of nomogram was accurate with AUC of 0.934 (95% confidence interval [CI]: 0.914-0.950) in testing cohort and 0.744 (95% CI: 0.699-0.785) in external validation cohort. The predictive accuracy of nomogram was better than that of previously proposed fistula risk scores both in testing and external validation cohort (all p < 0.05).
CONCLUSIONS: The novel nomogram based on three easily available parameters could accurately predict CR-POPF after PD. It would have high clinical value due to its accuracy and convenience.

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Mesh:

Year:  2020        PMID: 32901325     DOI: 10.1007/s00268-020-05773-y

Source DB:  PubMed          Journal:  World J Surg        ISSN: 0364-2313            Impact factor:   3.352


  4 in total

1.  Risk factors of clinically relevant postoperative pancreatic fistula after pancreaticoduodenectomy: A systematic review and meta-analysis.

Authors:  Biao Zhang; Qihang Yuan; Shuang Li; Zhaohui Xu; Xu Chen; Lunxu Li; Dong Shang
Journal:  Medicine (Baltimore)       Date:  2022-07-01       Impact factor: 1.817

2.  Differential Performance of Machine Learning Models in Prediction of Procedure-Specific Outcomes.

Authors:  Kevin A Chen; Matthew E Berginski; Chirag S Desai; Jose G Guillem; Jonathan Stem; Shawn M Gomez; Muneera R Kapadia
Journal:  J Gastrointest Surg       Date:  2022-05-04       Impact factor: 3.267

3.  Establishment and Verification of Prognostic Nomograms for Young Women With Breast Cancer Bone Metastasis.

Authors:  Zhan Wang; Haiyu Shao; Qiang Xu; Yongguang Wang; Yaojing Ma; Diarra Mohamed Diaty; Jiahao Zhang; Zhaoming Ye
Journal:  Front Med (Lausanne)       Date:  2022-04-12

4.  External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence.

Authors:  So Jeong Yoon; Wooil Kwon; Ok Joo Lee; Ji Hye Jung; Yong Chan Shin; Chang-Sup Lim; Hongbeom Kim; Jin-Young Jang; Sang Hyun Shin; Jin Seok Heo; In Woong Han
Journal:  Ann Surg Treat Res       Date:  2022-03-04       Impact factor: 1.859

  4 in total

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