Clinical Laboratory Blood Biomarker-Based Nomograms for Prediction of Lymph Node Metastasis and Prognosis in Resectable Esophagogastric Junction Adenocarcinoma: A Retrospective Diagnostic Study

Background: Esophagogastric junction adenocarcinoma (EJA) lacks blood-based predictive biomarkers for lymph node status and prognosis. We aimed to build nomograms with the preoperative blood biomarkers to predict lymph node metastasis (LNM) and prognosis in resectable EJA. Methods In this study, EJA patients who underwent surgery were collected from the Cancer Hospital of Shantou University Medical College between January 2010 and December 2017. The patients were divided into training cohort (n = 465) and validation cohort (n = 289) chronologically. 52 candidate biomarkers for nomogram construction included sociodemographic data and preoperative clinical laboratory blood baseline data. Lasso regression was used to build LNM prediction nomogram (LNM nomogram). Univariate and multivariate Cox regression analysis was applied to select factors for overall survival prediction nomogram (OS nomogram). Results As a result, for predicting LNM, the LNM nomogram containing seven biomarkers showed good discrimination and calibration ability, with C-indexes of 0.684 and 0.630 in the training and validation cohorts, respectively. Moreover, the OS nomogram for survival prediction composed of 12 factors yielded C-indexes of 0.652 and 0.663 in the training and validation cohorts, respectively. Kaplan-Meier survival analysis showed patients with high OS nomogram scores had worse 5-year OS than those with low scores (training cohort: 59.6% vs. 26.2%; validation cohort: 58.6% vs. 38.6%; all p < 0.0001). Conclusions In conclusion, these two nomograms constructed based on the clinical laboratory blood biomarkers are potential prediction models for lymph node status and survival of resectable EJA.