Clinical validation of scoring systems of postoperative pancreatic fistula after pancreatoduodenectomy: Applicability to Eastern cohorts?

Kang, Jae Seung; Park, Taesung; Han, Youngmin; Lee, Seungyeon; Kim, Jae Ri; Kim, Hongbeom; Kwon, Wooil; Kim, Sun‐Whe; Heo, Jin Seok; Choi, Seong‐Ho; Choi, Dong Wook; Kim, Song Cheol; Hong, Tae Ho; Yoon, Dong Sup; Park, Joon Seong; Park, Sang Jae; Han, Sung‐Sik; Choi, Se Yeon; Kim, Joo Seop; Lim, Chae‐Seok; Jang, Jin–Young

doi:10.1016/j.pan.2019.05.338

Cited by 9 publications

(16 citation statements)

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“…The resulting median overall survival exceeded 32 months, that is one of the longest reported survival rates after upfront resection for PDAC. [23][24][25][26] We can conclude that, in the setting of a high-volume center, a potential delay in accessing to surgery would seem not to negatively affect the prognosis of most patients. Despite providing several relevant insights, the present study has some limitations.…”

Section: Discussionmentioning

confidence: 99%

Does the surgical waiting list affect pathological and survival outcome in resectable pancreatic ductal adenocarcinoma?

Marchegiani

Andrianello

Perri

et al. 2018

HPB

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Section: Discussionmentioning

confidence: 99%

Does the surgical waiting list affect pathological and survival outcome in resectable pancreatic ductal adenocarcinoma?

Marchegiani

Andrianello

Perri

et al. 2018

HPB

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“…By combining preoperative albumin and creatine levels with postoperative DFA and CAR on PODs 2, 3 and 5, the predictive ability of our model has a better performance and a higher accuracy than the traditional static model, including the fistula risk score (FRS), as well as the followed-up modified alternate FRS (a-FRS) and ultra-alternate FRS (ua-FRS), which were all conducted The cells circled by red borders represented that theirs risk were higher than cut-off points in theirs corresponding time points. POD postoperative day, CAR C-reactive protein to albumin ratio, Cr creatine not so accurate enough on cohorts including Asian groups (AUC < 0.7) [18,27,28].…”

Section: Discussionmentioning

confidence: 99%

“…For most preoperative and intraoperative static indexes, our result shows that only a few of them could predict the occurrence of CR-POPF, apart from preoperative serum albumin and creatine levels. This is possibly due to the fact that there's still no strong consensus about the association between these factors and CR-POPF, which probably leads to the inconsistencies in the prediction models developed recently [9,10,16,18]. However, we noted that the patients who developed CR-POPF tend to have an advanced age [44,45], higher BMI [46,47], softer pancreas [48][49][50], and smaller pancreatic ducts [48,[51][52][53][54][55], were less likely to have diabetes [47,56], and were more likely to have had portal vein resection [57], which are comparable to findings of previous research.…”

Section: Discussionmentioning

confidence: 99%

“…Among them, postoperative drainage fluid amylase (DFA) and C-reactive protein-to-serum-albumin ratio (CAR) seemed to be the accurate and widely used indexes for the prediction of CR-POPF, especially in a particular time-point, in which they are suggested to be useful and critical predictive indexes [11][12][13][14]. However, preoperative and intraoperative factors indicating CR-POPF seemed to vary [15][16][17][18], furthermore, such prediction result cannot be updated according to the changes in the patient's fluctuating state and examination results over time.…”

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confidence: 99%

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Dynamic prediction for clinically relevant pancreatic fistula: a novel prediction model for laparoscopic pancreaticoduodenectomy

Liu

Cai

et al. 2021

BMC Surg

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Background With the recent emerge of dynamic prediction model on the use of diabetes, cardiovascular diseases and renal failure, and its advantage of providing timely predicted results according to the fluctuation of the condition of the patients, we aim to develop a dynamic prediction model with its corresponding risk assessment chart for clinically relevant postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy by combining baseline factors and postoperative time-relevant drainage fluid amylase level and C-reactive protein-to-albumin ratio. Methods We collected data of 251 patients undergoing LPD at West China Hospital of Sichuan University from January 2016 to April 2019. We extracted preoperative and intraoperative baseline factors and time-window of postoperative drainage fluid amylase and C-reactive protein-to-albumin ratio relevant to clinically relevant pancreatic fistula by performing univariate and multivariate analyses, developing a time-relevant logistic model with the evaluation of its discrimination ability. We also established a risk assessment chart in each time-point. Results The proportion of the patients who developed clinically relevant postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy was 7.6% (19/251); preoperative albumin and creatine levels, as well as drainage fluid amylase and C-reactive protein-to-albumin ratio on postoperative days 2, 3, and 5, were the independent risk factors for clinically relevant postoperative pancreatic fistula. The cut-off points of the prediction value of each time-relevant logistic model were 14.0% (sensitivity: 81.9%, specificity: 86.5%), 8.3% (sensitivity: 85.7%, specificity: 79.1%), and 7.4% (sensitivity: 76.9%, specificity: 85.9%) on postoperative days 2, 3, and 5, respectively, the area under the receiver operating characteristic curve was 0.866 (95% CI 0.737–0.996), 0.896 (95% CI 0.814–0.978), and 0.888 (95% CI 0.806–0.971), respectively. Conclusions The dynamic prediction model for clinically relevant postoperative pancreatic fistula has a good to very good discriminative ability and predictive accuracy. Patients whose predictive values were above 14.0%, 8.3%, and 7.5% on postoperative days 2, 3, and 5 would be very likely to develop clinically relevant postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy.

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“…The new strategy uses various predictive systems to enable early prediction and prevention and optimize individual treatment decisions[ 6 , 9 , 10 ]. Previous predictive systems[ 6 , 9 , 10 ] might reflect POPF incidence and had the merit of simplicity, but their predictive accuracy is somewhat questionable[ 11 , 12 ]. Therefore, to more accurately predict POPF, further research is needed.…”

Section: Introductionmentioning

confidence: 99%

Risk prediction platform for pancreatic fistula after pancreatoduodenectomy using artificial intelligence

Han¹,

Cho²,

Ryu³

et al. 2020

WJG

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BACKGROUND Despite advancements in operative technique and improvements in postoperative managements, postoperative pancreatic fistula (POPF) is a life-threatening complication following pancreatoduodenectomy (PD). There are some reports to predict POPF preoperatively or intraoperatively, but the accuracy of those is questionable. Artificial intelligence (AI) technology is being actively used in the medical field, but few studies have reported applying it to outcomes after PD. AIM To develop a risk prediction platform for POPF using an AI model. METHODS Medical records were reviewed from 1769 patients at Samsung Medical Center who underwent PD from 2007 to 2016. A total of 38 variables were inserted into AI-driven algorithms. The algorithms tested to make the risk prediction platform were random forest (RF) and a neural network (NN) with or without recursive feature elimination (RFE). The median imputation method was used for missing values. The area under the curve (AUC) was calculated to examine the discriminative power of algorithm for POPF prediction. RESULTS The number of POPFs was 221 (12.5%) according to the International Study Group of Pancreatic Fistula definition 2016. After median imputation, AUCs using 38 variables were 0.68 ± 0.02 with RF and 0.71 ± 0.02 with NN. The maximal AUC using NN with RFE was 0.74. Sixteen risk factors for POPF were identified by AI algorithm: Pancreatic duct diameter, body mass index, preoperative serum albumin, lipase level, amount of intraoperative fluid infusion, age, platelet count, extrapancreatic location of tumor, combined venous resection, co-existing pancreatitis, neoadjuvant radiotherapy, American Society of Anesthesiologists’ score, sex, soft texture of the pancreas, underlying heart disease, and preoperative endoscopic biliary decompression. We developed a web-based POPF prediction platform, and this application is freely available at . CONCLUSION This study is the first to predict POPF with multiple risk factors using AI. This platform is reliable (AUC 0.74), so it could be used to select patients who need especially intense therapy and to preoperatively establish an effective treatment strategy.

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Clinical validation of scoring systems of postoperative pancreatic fistula after pancreatoduodenectomy: Applicability to Eastern cohorts?

Cited by 9 publications

References 0 publications

Does the surgical waiting list affect pathological and survival outcome in resectable pancreatic ductal adenocarcinoma?

Does the surgical waiting list affect pathological and survival outcome in resectable pancreatic ductal adenocarcinoma?

Dynamic prediction for clinically relevant pancreatic fistula: a novel prediction model for laparoscopic pancreaticoduodenectomy

Risk prediction platform for pancreatic fistula after pancreatoduodenectomy using artificial intelligence

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