Construction and validation of a nomogram prediction model for early recurrence of patients undergoing radical pancreaticoduodenectomy for pancreatic ductal adenocarcinoma
10.3760/cma.j.cn113884-20221028-00404
- VernacularTitle:胰腺导管腺癌患者根治性PD术后早期复发列线图预测模型的构建与验证
- Author:
Yanwei WANG
1
;
Chenghao CUI
;
Mingtai LI
;
Yurong LIANG
Author Information
1. 解放军医学院，北京 100853
- Keywords:
Pancreatic neoplasms;
Pancreaticoduodenectomy;
Nomograms;
Early recurrence;
Decision curve analysis
- From:
Chinese Journal of Hepatobiliary Surgery
2023;29(7):538-543
- CountryChina
- Language:Chinese
-
Abstract:
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.
