Development of a Nomogram to Predict Clinically Relevant Postoperative Pancreatic Fistula After Pancreaticoduodenectomy on the Basis of Visceral Fat Area and Magnetic Resonance Imaging

The Value of Blood T Cell Frequencies for Risk Prediction of Postoperative Complications in Pancreatic Cancer Surgery

Objective

To quantify and characterize preoperative blood T cells in patients with pancreatic ductal adenocarcinoma (PDAC), who underwent tumor resection, and to determine their relevance as biomarkers for postoperative pancreas-specific complications.

Background

Pancreas-specific complications after pancreatic surgery are associated with a high morbidity and mortality, which both deprive patients of adjuvant chemotherapy. Noninvasive biomarkers for risk prediction of postoperative complications are missing, and the role of blood T cells for preoperative risk stratification is unknown.

Methods

The preoperative frequency of blood T cell subsets was analyzed for 73 patients with PDAC, who underwent proximal pancreatectomy. Patients were screened for postoperative complications such as pancreatic fistula, postpancreatectomy hemorrhage, and postpancreatectomy acute pancreatitis. The frequency of CD8+, conventional CD4+, and regulatory T cells, as well as the differentiation state of each T cell subset in the peripheral blood of patients with PDAC, was analyzed.

Results

Of 73 patients with PDAC, 19.2% developed pancreas-specific complications. The occurrence of postoperative complications was independent of the type of resection performed (Whipple procedure vs pylorus-preserving pancreaticoduodenectomy). Neither the frequency of CD8+, conventional CD4+, and regulatory T cells nor the state of T cell differentiation in the peripheral blood was associated with postoperative pancreas-specific complications. Notably, a significantly lower preoperative bilirubin serum level was observed in patients, who developed postpancreatectomy hemorrhage after proximal pancreatectomy (P =0.001).

Conclusions

A low preoperative bilirubin serum level was associated with a higher risk for postpancreatectomy hemorrhage after proximal pancreatectomy. However, the preoperative blood T cell frequency does not predict postoperative pancreas-specific complications.

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.

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.