A novel robust nomogram based on preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) for predicting lymph node metastasis of gastric cancer

Xu Wang; Qijin He; Huixi Liang; Jiani Liu; Xin Xu; Kui Jiang; Jie Zhang

doi:10.21037/jgo-21-507

A novel robust nomogram based on preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) for predicting lymph node metastasis of gastric cancer

J Gastrointest Oncol. 2021 Dec;12(6):2706-2718. doi: 10.21037/jgo-21-507.

Authors

Xu Wang^#¹, Qijin He^#¹, Huixi Liang¹, Jiani Liu¹, Xin Xu¹, Kui Jiang¹, Jie Zhang¹

Affiliation

¹ Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China.

^# Contributed equally.

Abstract

Background: Accurate assessment of lymph node status in gastric cancer (GC) patients can help to select appropriate treatment strategies for GC, but the diagnostic accuracy of conventional methods needs to be improved. The aim of this study was to investigate the predictive value of preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) on lymph node status in GC patients and to construct a risk prediction model.

Methods: This study retrospectively analyzed the clinicopathological characteristics of 349 patients with GC who underwent radical gastrectomy, among which 250 patients were recruited in the training cohort and 99 patients in the independent validation cohort. Significant risk factors in univariate analysis were further identified as independent variables in multivariate logistic regression analysis, which were then incorporated and presented in a nomogram. Receiver operating characteristic (ROC) curves, Calibration curve and decision curve analysis (DCA) curves were used to evaluate the discrimination, prediction accuracy and clinical effectiveness of the model.

Results: Multifactorial logistic regression analysis showed that alcohol use (OR =2.203, P=0.036), Depth of invasion (OR =7.756, P<0.001), differentiation (OR =2.252, P=0.018), carcinoembryonic antigen (CEA) (OR =2.443, P=0.017), carbohydrate antigen 19-9 (CA199) (OR =2.715, P=0.008) and HALP (OR =2.276, P=0.032) were independent risk factors for lymph node metastasis (LNM) in GC. We used these factors to construct a nomogram for predicting LNM in GC patients, and the ROC curves showed good discrimination of the model with AUC values of 0.854 (training cohort) and 0.868 (validation cohort), respectively, and the calibration curves showed good predictive ability of the nomogram, in addition to the DCA curves results showed the clinical usefulness of the model.

Conclusions: In conclusion, we established a nomogram for predicting LNM in patients with GC.

Keywords: Gastric cancer (GC); lymph node metastasis (LNM); nomogram; risk factors.