Development and multicenter validation of a nomogram for preoperative prediction of lymph node positivity in pancreatic cancer (NeoPangram)

Abstract

BackgroundNeoadjuvant therapy is associated with nodal downstaging and improved oncological outcomes in patients with lymph node (LN)-positive pancreatic cancer. This study aimed to develop and validate a nomogram to preoperatively predict LN-positive disease. MethodsA total of 558 patients with resected pancreatic cancer were randomly and equally divided into development and internal validation cohorts. Multivariate logistic regression analysis was used to construct the nomogram. Model performance was evaluated by discrimination, calibration, and clinical usefulness. An independent multicenter cohort consisting of 250 patients was used for external validation. ResultsA four-marker signature was built consisting of carbohydrate antigen 19–9 (CA19–9), CA125, CA50, and CA242. A nomogram was constructed to predict LN metastasis using three predictors identified by multivariate analysis: risk score of the four-marker signature, computed tomography-reported LN status, and clinical tumor stage. The prediction model exhibited good discrimination ability, with C-indexes of 0.806, 0.742 and 0.763 for the development, internal validation, and external validation cohorts, respectively. The model also showed good calibration and clinical usefulness. A cut-off value (0.72) for the probability of LN metastasis was determined to separate low-risk and high-risk patients. Kaplan-Meier survival analysis revealed a good agreement of the survival curves between the nomogram-predicted status and the true LN status. ConclusionsThis nomogram enables the identification of pancreatic cancer patients at high risk for LN positivity who may have more advanced disease and thus could potentially benefit from neoadjuvant therapy.