Analysis of risk factors and development of a nomogram model for early recurrence following curative resection of resectable pancreatic cancer
10.3760/cma.j.cn115667-20240520-00096
- VernacularTitle:可切除胰腺癌根治术后早期复发的危险因素分析及列线图模型构建
- Author:
Chengyu HU
1
;
Jianyu YANG
1
;
Yannan XU
1
;
Yifan YIN
1
;
Minwei YANG
1
;
Xueliang FU
1
;
Dejun LIU
1
;
Yanmiao HUO
1
;
Wei LIU
1
;
Junfeng ZHANG
1
;
Yongwei SUN
1
;
Rong HUA
1
Author Information
1. 上海交通大学医学院附属仁济医院胆胰外科，上海 200127
- Publication Type:Journal Article
- Keywords:
Pancreatic neoplasms;
Recurrence;
Risk factors;
Nomograms
- From:
Chinese Journal of Pancreatology
2025;25(2):104-111
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To identify independent risk factors for early recurrence following curative resection of resectable pancreatic cancer and establish a nomogram prediction model.Methods:Clinical data from 405 patients with resectable pancreatic cancer treated at Renji Hospital, Shanghai Jiao Tong University School of Medicine from February 2010 to December 2020 were retrospectively reviewed. Patients were stratified into a training cohort (265 patients form February 2010 to December 2018) and a validation cohort (140 patients from January 2019 to December 2020) based on surgery dates. Optimal cutoff values for clinical variables were determined using X-tile software. Independent risk factors were identified through univariate and multivariate Cox proportional hazards regression analyses. Kaplan-Meier curves for recurrence-free survival (RFS) were generated across subgroups, and a nomogram was developed to predict early recurrence (within 1 year post-surgery). Time-dependent receiver operating characteristic (tROC) curves was drawn and area under the curve (AUC) metrics were utilized to evaluate predictive accuracy, while model reliability was assessed by calibration curves. Individualized risk scores derived from the nomogram were stratified into high- and low-risk groups using X-tile-derived cutoff values. Survival differences between groups were analyzed via log-rank tests. The clinical application value was judged by decision curve analysis (DCA) compared to TNM staging. Results:In the training cohort, 139 patients (52.45%) experienced early recurrence, with a median RFS of 11.1 months [interquartile range ( IQR): 6.0-26.0]. The validation cohort reported 70 early recurrences (50.00%) and a median RFS of 11.8 months ( IQR: 4.9-21.4). Univariate analysis revealed significant associations between early recurrence and tumor diameter, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), systemic immune-inflammation index (SⅡ), and prognostic nutritional index (PNI). Multivariate analysis identified tumor diameter ≥3.75 cm ( HR=1.718, 95% CI 1.223-2.412, P=0.002), CA19-9≥218 U/ml ( HR=1.567, 95% CI 1.107-2.220, P=0.011), CA125≥20.98 U/ml ( HR=2.501, 95% CI 1.768-3.539, P<0.001), SⅡ≥388.28 ( HR=1.708, 95% CI 1.096-2.662, P=0.018), and PNI<53.18 ( HR=0.596, 95% CI 0.404-0.879, P=0.009) as independent risk factors for early recurrence. The nomogram achieved AUC values of 0.771 and 0.708 in the training and validation cohorts, respectively. Calibration curves demonstrated strong agreement between predicted and observed survival probabilities. Kaplan-Meier analysis revealed significantly lower 1-year RFS rates in high-risk versus low-risk groups for both cohorts (training: HR=3.65, 95% CI 2.45-5.44, P<0.001; validation: HR=2.37, 95% CI 1.39-4.06, P=0.001). DCA indicated superior net benefit of the nomogram over TNM staging across threshold probabilities of 0.2-0.9. Conclusions:The proposed nomogram effectively integrates clinical and serological biomarkers to preoperatively assess early recurrence risk in resectable pancreatic cancer patients, offering enhanced precision for clinical decision-making.
