Nomogram for predicting the preoperative lymph node metastasis in resectable pancreatic cancer

Abstract

Background: Lymph node metastasis (LNM) is a critical prognostic factor in resectable pancreatic cancer (PC) patients, determining treatment strategies. This study aimed to develop a clinical model to adequately and accurately predict the risk of LNM in PC patients.

Methods: 13,200 resectable PC patients were enrolled from the SEER (Surveillance, Epidemiology, and End Results) database, and randomly divided into a training group and an internal validation group at a ratio of 7:3. An independent group (n = 62) obtained from The First Affiliated Hospital of Xinxiang Medical University was enrolled as the external validation group. The univariate and multivariate logistic regression analyses were used to screen independent risk factors for LNM. The minimum Akaike's information criterion (AIC) was performed to select the optimal model parameters and construct a nomogram for assessing the risk of LNM. The performance of the nomogram was assessed by the receiver operating characteristics (ROC) curve, calibration plot, and decision curve analysis (DCA). In addition, an online web calculator was designed to assess the risk of LNM.

Result: A total of six risk predictors (including age at diagnosis, race, primary site, grade, histology, and T-stage) were identified and included in the nomogram. The areas under the curves (AUCs) [95% confidential interval (CI)] were 0.711 (95%CI: 0.700-0.722), 0.700 (95%CI: 0.683-0.717), and 0.845 (95%CI: 0.749-0.942) in the training, internal validation and external validation groups, respectively. The calibration curves showed satisfied consistency between nomogram-predicted LNM and actual observed LNM. The concordance indexes (C-indexes) in the training, internal, and external validation sets were 0.689, 0.686, and 0.752, respectively. The DCA curves of the nomogram demonstrated good clinical utility.

Conclusion: We constructed a nomogram model for predicting LNM in pancreatic cancer patients, which may help oncologists and surgeons to choose more individualized clinical treatment strategies and make better clinical decisions.

Keywords: Lymph node metastasis; Nomogram; Preoperative; Resectable pancreatic cancer; SEER.

Fig. 1

Patients enrollment and exclusion process in the SEER database

Fig. 2

The nomogram for the risk of lymph node metastasis in resectable pancreatic cancer patients

Fig. 3

ROC of the nomogram for the training cohort (A), the internal validation cohort (B), and the external validation cohort (C)

Fig.4

The calibration plots of the training cohort (A), the internal validation cohort (B), and the external validation cohort (C)

Fig.5

Nomogram decision curves (DCA) for the training cohort (A), the internal validation cohort (B), and the external validation cohort (C)

Fig. 6

The Kaplan–Meier overall survival (OS) analysis of lymph node metastasis in the training set (A), the internal validation set (B), and the external validation set (C)