A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer - Wu, Hongyu; Liu, Wen; Yin, Minyue; Liu, Lu; Qu, Shuting; Xu, Wei; Xu, Chunfang (Frontiers in Oncology, 2023)
Background: Preoperative assessment of the presence of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) remains difficult. We aimed to develop a practical prediction model based on preoperative pathological data and inflammatory or nutrition-related indicators. Methods: This study retrospectively analyzed the clinicopathological characteristics of 1061 patients with EGC who were randomly divided into training set and validation set at a ratio of 7:3. In the training set, we introduced LASSO algorithm and multivariate logistic regression to identify independent risk factors and construct the nomogram. Both internal and external validation were performed by AUC, C-index, calibration curve and DCA. Results: LNM occurred in 162 of 1061 patients, and the rate of LNM was 15.27%. In the training set, four variables proved to be independent risk factors (P<0.05) and were incorporated into the final model, including depth of invasion, tumor size, degree of differentiation and platelet-tolymphocyte ratio (PLR). The AUC values were 0.775 and 0.792 for the training and validation groups, respectively. Both calibration curves showed great consistency in the predictive and actual values. Hosmer-Lemeshow (H-L) test was carried out in two cohorts, showing excellent performance with p-value>0.05 (0.684422, 0.7403046). Decision curve analysis demonstrated a good clinical benefit in the respective set. Conclusion: We established a preoperative nomogram including depth of invasion, tumor size, degree of differentiation and platelet-to-lymphocyte ratio (PLR) to predict LNM in EGC patients and achieved a good performance.