RESUMO
Objective:To study the risk factors for early recurrence of patients undergoing radical pancreaticoduodenectomy (PD) for pancreatic ductal adenocarcinoma (PDAC) and construct a normogram model.Methods:Patients undergoing open radical PD for PDAC at Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital from January 2014 to December 2021 were retrospectively screened. A total of 213 patients were enrolled, including 145 males and 68 females, aged (58.4±9.8) years. Patients were divided into the early recurrence group ( n=59, recurrence within 6 months after surgery) and a control group ( n=154, no recurrence within 6 months after surgery). Using minimum absolute value convergence and selection operator regression (LASSO) and multi-factor logistic regression analysis, we screened out the best predictor of early recurrence after PD for PDAC, and then established a nomogram model. The effectiveness of the model was validated by receiver operating characteristic (ROC) curve, calibration curves, and decision analysis curves. Results:Multivariate logistic regression analysis showed that patients with obstructive jaundice, vascular invasion, massive intraoperative bleeding, high-risk tumors (poorly differentiated or undifferentiated), high carbohydrate antigen 19-9 to total bilirubin ratio, and high fibrinogen and neutrophil to lymphocyte ratio scores had a higher risk of early postoperative recurrence. Based on the indexes above, a nomogram prediction model was constructed. The area under the ROC curve was 0.797 (95% CI: 0.726-0.854). Validation of the calibration curve exhibited good concordance between the predicted probability and ideal probability, decision curve analysis showed that the net benefits of the groupings established according to the model were all greater than 0 within the high risk threshold of 0.08 to 1.00. Conclusion:The nomogram for predicting early recurrence after PD for PDAC has a good efficiency, which could be helpful to screen out the high-risk patients for adjuvant or neoadjuvant therapy.
RESUMO
Objective:To study the differences in preoperative examination indexes between pancreatic head cancer and distal bile duct cancer, and to establish a preliminary prediction model to provide reference for clinical decision-making.Methods:Retrospective analysis was conducted on 243 consecutive patients who underwent open radical pancreaticoduodenectomy from January 1, 2015 to December 31, 2019 at the Chinese PLA General Hospital. There were 177 males and 66 females, aged (58.9±8.9) years old. Based on postoperative pathological results, these 243 patients were divided into the pancreatic head cancer group ( n=113) and the distal bile duct cancer group ( n=130). The clinical data of the two groups were collected. Minimum absolute value convergence and selection operator regression were used to screen the best predictors of pancreatic head cancer. The rms package was used to construct the nomogram model, and k-fold cross was used for internal validation. Results:Seven best predictive indexes are selected: age, rate of weight loss, main pancreatic duct diameter, neutrophil/lymphocyte, DTR (DBil/TBil), carcinoembryonic antigen and CA125. Based on these indexes, a nomogram prediction model was constructed with the C-index of 0.868 after k-fold cross-validation, indicating that discrimination of the model to be acceptable. Validation using calibration curve exhibited good concordance between the predicted probability with the ideal probability ( P=0.728). Conclusion:The nomogram prediction model established in this study effectively predicted patients with pancreatic head cancer, and helped preoperatively to differentiate pancreatic head cancer from distal cholangiocarcinoma.