Risk Models for Developing Pancreatic Fistula After Pancreatoduodenectomy: Validation in a Nationwide Prospective Cohort

Predicting postoperative pancreatic fistula after robotic pancreatoduodenectomy using International Study Group on Pancreatic Surgery and fistula risk scores: European multicentre retrospective cohort study

BACKGROUND

Postoperative pancreatic fistula represents the leading cause of morbidity and mortality after robotic pancreatoduodenectomy. Various scores have been proposed to stratify patients based on their postoperative pancreatic fistula risk, including three fistula risk scores, and two International Study Group for Pancreatic Surgery scores. This study compares the performance of these scores in patients undergoing robotic pancreatoduodenectomy.

METHODS

This is a multicentre European retrospective study in consecutive patients receiving robotic pancreatoduodenectomy for all indications (April 2014 to December 2021). The performance of the International Study Group for Pancreatic Surgery 4-tier (A-D) risk score, and its 3-tier (A-C) modification (International Study Group for Pancreatic Surgery 3-tier), fistula risk scores, alternative-fistula risk scores and the updated alternative-fistula risk scores in postoperative pancreatic fistula grade B/C prediction were compared based on their discrimination (area under the curve), calibration and clinical utility, evaluated through decision curve analyses.

RESULTS

Overall, 919 patients undergoing robotic pancreatoduodenectomy were included. The rate of grade B/C postoperative pancreatic fistula was 22.2% (n = 204). The area under the curve for the five scores differed only slightly: International Study Group for Pancreatic Surgery 0.63 (95% confidence interval (c.i.) 0.58 to 0.67), International Study Group for Pancreatic Surgery 3-tier 0.63 (95% c.i. 0.58 to 0.67), fistula risk scores 0.65 (95% c.i. 0.61 to 0.69), alternative-fistula risk scores 0.64 (95% c.i. 0.60 to 0.68) and updated alternative-fistula risk scores 0.65 (95% c.i. 0.60 to 0.69). The International Study Group for Pancreatic Surgery, International Study Group for Pancreatic Surgery 3-tier, fistula risk scores and alternative-fistula risk scores underestimated the risk of postoperative pancreatic fistula. In contrast, the updated alternative-fistula risk score was well-calibrated at low predicted risks, but overestimated postoperative pancreatic fistula risk for high-risk patients. In decision curve analyses, the updated alternative-fistula risk score showed a higher clinical utility compared with the four other risk scores.

CONCLUSION

The clinical utility of the updated alternative-fistula risk score for robotic pancreatoduodenectomy slightly outperformed the four other fistula risk scores, and might be used for patient counselling and patient stratification in clinical practice and research.

Baseline Body Composition and 3D-Extracellular Volume Fraction for Predicting Pancreatic Fistula after Distal Pancreatectomy in Pancreatic Body and/or Tail Adenocarcinoma

RATIONALE AND OBJECTIVES

Clinically relevant postoperative pancreatic fistula (CR-POPF) is a threatening complication in body and/or tail pancreatic ductal adenocarcinoma (PDAC) receiving distal pancreatectomy (DP) and is difficult to predict preoperatively. We aimed to identify the role of baseline CT-based body composition analysis and extracellular volume (ECV) map in predicting the risk of CR-POPF preoperatively.

MATERIALS AND METHODS

A total of 329 resectable PDAC patients were enrolled and underwent multiphasic contrast-enhanced CT. Body composition indicators were calculated, and ECV maps were generated through multiphasic CT images. The differences in clinical variables and quantitative parameters between CR-POPF and non-CR-POPF patients were compared. Correlations between ECV fraction and pancreatic fibrosis stage were analyzed. Multivariate logistic regression was performed to screen the independent predictors and develop prediction models for CR-POPF. Receiver operating characteristic curve was utilized to evaluate the predictive performance.

RESULTS

Among 329 patients, 19.76% (65/329) developed CR-POPF. Albumin, pancreatic texture, and intraoperative blood loss were used to build the clinical model with an AUC of 0.764. ECV fraction and total muscle ratio (TMR) were chosen to build the radiological model with an AUC of 0.872. A combined nomogram integrated with albumin, ECV fraction, and TMR could significantly improve the discrimination ability to an AUC of 0.924 (Delong test, all p < 0.05). The ECV fraction showed high positive correlation with histological fibrosis grade (Spearman ρ = 0.81).

CONCLUSION

CT-based body composition analysis and ECV exhibited great potential for predicting CR-POPF in body and/or tail PDAC after DP. The combined nomogram could further improve the predictive performance.

Risk stratification of postoperative pancreatic fistula and other complications following pancreatoduodenectomy. How far are we? A scoping review

PURPOSE

Pancreatoduodenectomy (PD) is a challenging procedure which is associated with high morbidity rates. This study was performed to make an overview of risk factors included in risk stratification methods both logistic regression models and models based on artificial intelligence algorithms to predict postoperative pancreatic fistula (POPF) and other complications following PD and to provide insight in the extent to which these tools were validated.

METHODS

Five databases were searched to identify relevant studies. Calculators, equations, nomograms, and artificial intelligence models that addressed POPF and other complications were included. Only PD resections were considered eligible. There was no exclusion of the minimally invasive techniques reporting PD resections. All other pancreatic resections were excluded.

RESULTS

90 studies were included. Thirty-five studies were related to POPF, thirty-five studies were related to other complications following PD and twenty studies were related to artificial intelligence predication models after PD. Among the identified risk factors, the most used factors for POPF risk stratification were the main pancreatic duct diameter (MPD) (80%) followed by pancreatic texture (51%), whereas for other complications the most used factors were age (34%) and ASA score (29.4%). Only 26% of the evaluated risk stratification tools for POPF and other complications were externally validated. This percentage was even lower for the risk models using artificial intelligence which was 20%.

CONCLUSION

The MPD was the most used factor when stratifying the risk of POPF followed by pancreatic texture. Age and ASA score were the most used factors for the stratification of other complications. Insight in clinically relevant risk factors could help surgeons in adapting their surgical strategy and shared decision-making. This study revealed that the focus of research still lies on developing new risk models rather than model validation, hampering clinical implementation of these tools for decision support.

Updating the paradigm of prophylactic abdominal drainage following pancreatoduodenectomy

BACKGROUND

Prophylactic abdominal drainage (PAD) is considered a routine procedure after pancreatoduodenectomy (PD) to prevent and detect severe complications at an early stage. However, the drainage itself may cause adverse consequences. Thus, the optimal strategy of PAD after PD remains controversial.

METHODS

The present paper summarizes the latest research on the strategies of PAD following PD, mainly focusing on 1) the selective placement of PAD, 2) the optimal drainage types, 3) the early removal of drainage (EDR), and 4) novel strategies for PAD management.

RESULTS

Accurate stratifications based on the potential risk factors of clinically relevant-postoperative pancreatic fistula (CR-POPF) facilitates the selective placement of PAD and the implementation of EDR, with postoperative outcomes superior or similar to routine PAD placement. Both active and passive drainage methods are feasible in most patients after PD, with similar prognostic outcomes. Novel predictive models with accurate, dynamic, and individualized performance further guide the management of PAD and afford a better prognosis.

CONCLUSIONS

Evidence-based risk stratification of CR-POPF aids in the management of PAD in patients undergoing PD. Novel dynamic and individualized PAD strategies might be the next hotspot in drain-relevant explorations.

Influence of pancreatic fistula on survival after upfront pancreatoduodenectomy for pancreatic ductal adenocarcinoma: multicentre retrospective study

BACKGROUND

The effects of postoperative pancreatic fistula on survival rates remain controversial. The aim of the present study was to evaluate the influence of postoperative pancreatic fistula on overall survival and recurrence-free survival after upfront pancreatoduodenectomy for pancreatic ductal adenocarcinoma.

METHODS

Patients operated on between January 2007 and December 2017 at seven tertiary pancreatic centres for pancreatic ductal adenocarcinoma were included in the study. Postoperative pancreatic fistula was defined using the 2016 International Study Group on Pancreatic Surgery grading system. The impact of postoperative pancreatic fistula on overall survival, recurrence-free survival (excluding 90-day postoperative deaths) and corresponding risk factors were investigated by univariable and multivariable analyses. Comparisons between groups were made using the chi-squared or Fisher's exact test for categorical variables and the Mann-Whitney U test for continuous variables. Odds ratios were estimated with their 95% confidence intervals. Survival rates were calculated using the Kaplan-Meier method with their 95% confidence intervals.

RESULTS

A total of 819 patients were included between 2007 and 2017. Postoperative pancreatic fistula occurred in 14.4% (n = 118) of patients; of those, 7.8% (n = 64) and 6.6% (n = 54) accounted for grade B and grade C postoperative pancreatic fistula respectively. The 5-year overall survival was 37.0% in the non-postoperative pancreatic fistula group and 45.3% in the postoperative pancreatic fistula cohort (P = 0.127). Grade C postoperative pancreatic fistula (excluding 90-day postoperative deaths) was not a prognostic factor for overall survival. The 5-year recurrence-free survival was 26.0% for patients without postoperative pancreatic fistula and 43.7% for patients with postoperative pancreatic fistula (P = 0.003). Eight independent prognostic factors for recurrence-free survival were identified: age over 70 years, diabetes, moderate or poor tumour differentiation, T3/T4 tumour stage, lymph node positive status, resection margins R1, vascular emboli and perineural invasion.

CONCLUSION

This high-volume cohort showed that grade C postoperative pancreatic fistula, based on the 2016 International Study Group on Pancreatic Surgery grading system, does not impact overall or recurrence-free survival (excluding 90-day postoperative deaths).

Optimal cutoff values of drain amylase for predicting pancreatic fistula are different between open and laparoscopic distal pancreatectomy

BACKGROUND

Drainage fluid amylase (DFA) is useful for predicting clinically relevant postoperative pancreatic fistula (CR-POPF) after distal pancreatectomy (DP). However, difference in optimal cutoff value of DFA for predicting CR-POPF between open DP (ODP) and laparoscopic DP (LDP) has not been investigated. This study aimed to identify the optimal cutoff values of DFA for predicting CR-POPF after ODP and LDP.

METHODS

Data for 294 patients (ODP, n = 127; LDP, n = 167) undergoing DP at Kobe University Hospital between 2010 and 2021 were reviewed. Propensity score matching was performed to minimize treatment selection bias. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cutoff values of DFA for predicting CR-POPF for ODP and LDP. Logistic regression analysis for CR-POPF was performed to investigate the diagnostic value of DFA on postoperative day (POD) three with identified cutoff value.

RESULTS

In the matched cohort, CR-POPF rates were 24.7% and 7.9% after ODP and LDP, respectively. DFA on POD one was significantly lower after ODP than after LDP (2263 U/L vs 4243 U/L, p < 0.001), while the difference was not significant on POD three (543 U/L vs 1221 U/L, p = 0.171). ROC analysis revealed that the optimal cutoff value of DFA on POD one and three for predicting CR-POPF were different between ODP and LDP (ODP, 3697 U/L on POD one, 1114 U/L on POD three; LDP, 10564 U/L on POD one, 6020 U/L on POD three). Multivariate analysis showed that DFA on POD three with identified cutoff value was the independent predictor for CR-POPF both for ODP and LDP.

CONCLUSIONS

DFA on POD three is an independent predictor for CR-POPF after both ODP and LDP. However, the optimal cutoff value for it is significantly higher after LDP than after ODP. Optimal threshold of DFA for drain removal may be different between ODP and LDP.

Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives

Postoperative pancreatic fistula (POPF) is a frequent complication after pancreatectomy, leading to increased morbidity and mortality. Optimizing prediction models for POPF has emerged as a critical focus in surgical research. Although over sixty models following pancreaticoduodenectomy, predominantly reliant on a variety of clinical, surgical, and radiological parameters, have been documented, their predictive accuracy remains suboptimal in external validation and across diverse populations. As models after distal pancreatectomy continue to be progressively reported, their external validation is eagerly anticipated. Conversely, POPF prediction after central pancreatectomy is in its nascent stage, warranting urgent need for further development and validation. The potential of machine learning and big data analytics offers promising prospects for enhancing the accuracy of prediction models by incorporating an extensive array of variables and optimizing algorithm performance. Moreover, there is potential for the development of personalized prediction models based on patient- or pancreas-specific factors and postoperative serum or drain fluid biomarkers to improve accuracy in identifying individuals at risk of POPF. In the future, prospective multicenter studies and the integration of novel imaging technologies, such as artificial intelligence-based radiomics, may further refine predictive models. Addressing these issues is anticipated to revolutionize risk stratification, clinical decision-making, and postoperative management in patients undergoing pancreatectomy.