Identifying the risk factors for pancreatic fistula after laparoscopic pancreaticoduodenectomy in patients with pancreatic cancer

Predictive role of the prognostic nutritional index for long-term prognosis among patients undergoing pancreatoduodenectomy: a meta-analysis

PURPOSE

To identify the predictive role of the preoperative prognostic nutritional index (PNI) for long-term survival in patients undergoing pancreatoduodenectomy.

METHODS

The PubMed, EMBASE, Web of Science, Cochrane Library and CNKI databases were searched up to October 28, 2024. The primary outcomes included overall survival (OS) and disease-free survival (DFS). Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated, and subgroup analyses by country, type of cancer and source of HR were performed.

RESULTS

Fifteen studies with 2106 patients were included. The pooled results demonstrated that a lower preoperative PNI was related to poorer OS (HR = 1.60, 95% CI: 1.38-1.86, P < 0.001) and DFS (HR = 1.44, 95% CI: 1.00-2.07, P = 0.051). Subgroup analysis stratified by country (China vs. non-China), type of cancer (pancreatic cancer vs. nonpancreatic cancer vs. mixed) and source of HR (univariate vs. multivariate analysis) revealed similar results.

CONCLUSION

On the basis of the available evidence, the preoperative PNI might serve as a novel prognostic indicator in patients undergoing pancreatoduodenectomy, with a lower PNI predicting worse survival. However, more high-quality studies are needed to further verify the above findings.

Computed tomography-based radiomics and body composition analysis for predicting clinically relevant postoperative pancreatic fistula after pancreaticoduodenectomy

Background

Preoperative risk assessment of clinically relevant postoperative pancreatic fistula (CR-POPF) is still lacking. This study aimed to develop and validate a combined model based on radiomics, pancreatic duct diameter, and body composition analysis for the prediction of CR-POPF in patients undergoing pancreaticoduodenectomy (PD).

Methods

Multivariable logistic regression was used to construct a combined model in conjunction with radiomics score (Rad-score), pancreatic duct diameter, and visceral fat area/total abdominal muscle area index (VFA/TAMAI). The models were internally validated using 1,000 bootstrap resamples. The predictive performance of these models was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results

The preoperative combined model was validated by 1,000 bootstrap resampling with the area under the ROC curve (AUC) of 0.839 (95% confidence interval: 0.757-0.907). The calibration curves and DCA showed that the combined model outperformed the clinical model and radiomics model. The combined model was presented as a web-based calculator (https://whyyjyljz.shinyapps.io/DynNomapp/).

Conclusions

We explored a method of combining radiomics features, pancreatic duct diameter, and body composition analysis predictors in preoperative assessment for risk of CR-POPF and developed a combined model that showed relatively good performance, but future studies with a larger sample size are needed to verify the stability and generalizability of this model.