Construction of a nomogram for preoperative prediction of the risk of lymph node metastasis in early gastric cancer

Abstract

BackgroundThe status of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) is particularly important for the formulation of clinical treatment. The purpose of this study was to construct a nomogram to predict the risk of LNM in EGC before operation.MethodsUnivariate analysis and logistic regression analysis were used to determine the independent risk factors for LNM. The independent risk factors were included in the nomogram, and the prediction accuracy, discriminant ability and clinical practicability of the nomogram were evaluated by the receiver operating characteristic curve (ROC), calibration curve and clinical decision curve (DCA), and 100 times ten-fold cross-validation was used for internal validation.Results33 (11.3%) cases of AGC were pathologically confirmed as LNM. In multivariate analysis, T stage, presence of enlarged lymph nodes on CT examination, carbohydrate antigen 199 (CA199), undifferentiated histological type and systemic inflammatory response index (SIRI) were risk factors for LNM. The area under the ROC curve of the nomogram was 0.86, the average area under the ROC curve of the 100-fold ten-fold cross-validation was 0.85, and the P value of the Hosmer-Lemeshow test was 0.60. In addition, the clinical decision curve, net reclassification index (NRI) and Integrated Discriminant Improvement Index (IDI) showed that the nomogram had good clinical utility.ConclusionsWe found that SIRI is a novel biomarker for preoperative prediction of LNM in EGC, and constructed a nomogram for preoperative prediction of the risk of LNM in EGC, which is helpful for the formulation of the clinical treatment strategies.

Computed Tomography–Based Predictive Model for the Probability of Lymph Node Metastasis in Gastric Cancer: A Meta-analysis

“…30 In addition to LN size, other variables such as T staging, histological subtype, level of differentiation, levels of tumor biomarkers, and endoscopic findings can all be associated with GC patient LNM status. 11,12,15,20,24,25 The depth of tumor invasion is associated with the duration of tumor growth, with deeper invasion corresponding to elevated odds of LNM. 20 The biological characteristics of undifferentiated and mixed GC cases are more unfavorable and related to higher odds of LNM.…”

“…11,12,15,20,24,25 The depth of tumor invasion is associated with the duration of tumor growth, with deeper invasion corresponding to elevated odds of LNM. 20 The biological characteristics of undifferentiated and mixed GC cases are more unfavorable and related to higher odds of LNM. [31][32][33] Predictive models incorporating these factors can thus be used to comprehensively evaluate GC patient LNM status.…”

“…Details regarding the CT-based predictive models used in these studies are shown in Table 2. Four studies 14,18,21,22 incorporated radiomics data, while seven [11][12][13]15,16,20,23 incorporated biomarker data. Table 2 includes details regarding the TP, TN, FP, and FN values for each study.…”

“…The results of quality analyses for the included studies are shown in Figure 2. Of these studies, 12 failed to disclose whether patients were continuously enrolled, [11][12][13][14][15][16][17][18]20,22,23,25 while 11 failed to clarify the blinding methods used. 12,13,[16][17][18][19][20][22][23][24][25]…”

“…10 Lymph node sizing is thus often evaluated in light of other factors including serum measurements, tumor T staging, histological type, iodine concentration value based on the dual-energy CT, and radiomics scores with the goal of achieving a higher degree of accuracy when preoperatively assessing GC patient LNM status. [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] The concept of imaging biomarkers was raised by Gabelloni et al 26 The imaging biomarkers can provide anatomical and/or functional parameters that correlate with histopathological or molecular data. 26 Therefore, imaging biomarkers can provide a significant added value to conventional imaging for improving T and N staging of GC and predicting treatment response and overall prognosis, possibly leading to better patient outcomes.…”