Establishment of Decision Rules and Risk Assessment Model for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer

Abstract

Background: Preoperative accurate prediction of lymph node status is especially important for the formulation of treatment plans for patients with gastric cancer (GC). The purpose of this study was to establish decision rules and a risk assessment model for lymph node metastasis (LNM) in GC using preoperative indicators. Methods: The clinical data of 554 patients who underwent gastrectomy with D2 lymphadenectomy were collected. A 1:1 propensity score matching (PSM) system was used, and the clinical data of the matched 466 patients were further analyzed. The important risk factors for LNM were extracted by the random forest algorithm, and decision rules and nomogram models for LNM were constructed with a classification tree and the “rms” package of R software, respectively. Results: Tumor size ( OR : 2.058; P = 0.000), computed tomography (CT) findings ( OR : 1.969; P = 0.001), grade ( OR : 0.479; P = 0.000), hemoglobin (Hb) ( OR : 1.211; P = 0.005), CEA ( OR : 1.111; P = 0.017), and CA19-9 ( OR : 1.040; P = 0.033) were independent risk factors for LNM in GC. Tumor size did rank first in the ranking of important factors for LNM in GC and was the first-level segmentation of the two initial branches of the classification tree. The accuracy, sensitivity, specificity, and positive predictive value of the decision rules in diagnosing preoperative LNM in GC were 75.6, 85.7, 73.9, 73.5, and 79.3%, respectively. The accuracy, sensitivity, and specificity of the risk assessment model in predicting preoperative LNM in GC were 79.3, 80.3, and 79.4%, respectively. Conclusion: Tumor size was the most important factor for evaluating LNM in GC. This decision rules and nomogram model constructed to take into account tumor size, CT findings, grade, hemoglobin, CEA, and CA19-9 effectively predicted the incidence of LNM in preoperative GC.

Radiomics model based on preoperative 18F-fluorodeoxyglucose PET predicts N2-3b lymph node metastasis in gastric cancer patients

“…After consulting a large number of literature, we consider the easily and simply tumor markers (CA19-9 and CEA) as major clinical risk factors. Existing studies have shown that CEA level was a significant predictive marker for the N stage in patients with GC [27,28]. In our study, the results also suggested that CEA level was an important predictive factor besides the PET Rad-score according to AIC.…”

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

“…In addition, long-term alcohol consumption can lead to violation of the protein synthesis function of liver, followed by the development of lower nutritional levels. This study also found that the degree of tumor differentiation and depth of infiltration were independent risk factors for LNM, which showed great similarity with the results of other studies (34)(35)(36).…”

A model of multiple tumor marker for lymph node metastasis assessment in colorectal cancer: a retrospective study

“…In the clinical-radiomics nomogram model for LNM prediction in CRC developed by Li et al (2020) , CA19-9 has greater weight of feature coefficients than CEA. Huang et al (2020) have also revealed that CA19-9 has higher AUC than CEA for LNM assessment in gastric cancer. These findings parallel the results displayed in Tables S4 of our study.…”