Construction and validation of a prognostic nomogram based on lipid parameters for pancreatic cancer patients undergoing postoperative adjuvant chemotherapy
10.3760/cma.j.cn115667-20240820-00134
- VernacularTitle:基于血脂参数的胰腺癌术后辅助化疗患者预后列线图的构建及验证
- Author:
Jinyue LIU
1
;
Xue JING
1
;
Shijin WANG
1
;
Libin LIU
1
;
Jianrui ZHOU
1
;
Yueping JIANG
1
Author Information
1. 青岛大学附属医院消化内科，青岛 266000
- Publication Type:Journal Article
- Keywords:
Pancreatic neoplasms;
Chemoradiotherapy, adjuvant;
Plasma lipid;
Nomogram
- From:
Chinese Journal of Pancreatology
2025;25(2):112-118
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish and validate a lipid parameter-based prognostic model for predicting recurrence free survival (RFS) in pancreatic cancer patients receiving postoperative adjuvant chemotherapy.Methods:A retrospective analysis was conducted on the clinical and pathological data of 155 patients who underwent pancreatic cancer resection followed by adjuvant chemotherapy at Affiliated Hospital of Qingdao University between January 2019 and December 2022. The patients were randomly divided into a training set ( n=108) and a validation set ( n=47) in a 7∶3 ratio. X-tile software was used to determine cutoff values for lipid parameters. Univariate and multivariate Cox regression analyses were performed to construct a model predicting RFS, which was then visualized using a nomogram. The model's predictive performance, accuracy and stability, and clinical application value were evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA), respectively. Individual risk scores for recurrence were calculated based on the nomogram model, and X-tile software was employed to identify optimal cutoff values for risk stratification, which was used to divide patients into low-risk and high-risk groups. Survival differences between two groups were analyzed using survival curves. Results:Among lipid parameters, patients with higher apolipoprotein A1 level had obviously longer RFS than those with low apolipoprotein A1 level (10.17 months vs 8.92 months, HR=0.397, 95% CI 0.237~0.664); patients with high total cholesterol level had obviously shorter RFS than those with low total cholesterol level (8.33 months vs 16.27months, HR=3.382, 95% CI 1.901~5.824) ; patients with high low-density lipoprotein level had obviously shorter RFS than those with low low-density lipoprotein level (8.53 months vs 11.43 months, HR=1.617, 95% CI 1.013~2.582) ; patients with high lipoprotein(a) had shorter RFS than those with low lipoprotein(a) (8.53 months vs 14.43 months, HR=2.640, 95% CI 1.514-4.604) ; and all the differences were statistical significant (all P value <0.05). Univariate Cox regression analysis identified advanced T stage, advanced N stage, high total cholesterol level, high low-density lipoprotein level, low apolipoprotein A1 level, high apolipoprotein B level, and high lipoprotein(a) level as risk factors for RFS. Multivariate Cox regression analysis revealed that tumors located in the pancreatic body or tail ( HR=0.63, 95% CI 0.36-0.86, P=0.042), advanced T stage ( HR=4.85, 95% CI 1.47-16.04, P=0.010), advanced N stage ( HR=0.48, 95% CI 0.26-0.87, P=0.015), elevated total cholesterol levels ( HR=3.61, 95% CI 1.46-8.91, P=0.005), high density lipoprotein levels ( HR=0.48, 95% CI 0.26-0.87, P=0.015), and elevated lipoprotein(a) levels ( HR=3.17, 95% CI 1.61-6.24, P<0.001) were independent risk factors for RFS. The nomogram model incorporating these six factors above demonstrated an AUC of 0.78 (95% CI 0.70-0.87) in the training set and 0.75 (95% CI 0.59-0.91) in the validation set. Calibration curves indicated a high degree of agreement between predicted and observed outcomes. DCA suggested that the model provides substantial clinical benefit. Kaplan-Meier survival curve analysis showed that patients in the high-recurrence risk group from training set and validation set both had significantly shorter RFS compared to those in the low-recurrence risk group (6.93 months vs 12.13 months, HR=4.024, 95% CI 2.594-6.243; 6.85 months vs 11.93 months, HR=2.314, 95% CI 1.227-4.362); and all the differences were statistical significant (all P value <0.05). Conclusions:The nomogram model based on lipid parameters can effectively predict recurrence free survival in patients undergoing adjuvant chemotherapy after pancreatic cancer surgery.
