[Establishment of a nomogram model for predicting lymph node metastasis in patients with cN0 gastric cancer based on combination of preoperative C-reactive protein/albumin ratio].

Objective: To investigate the relationship between systemic inflammatory markers such as neutrophil/lymphocyte ratio (NLR) and C-reactive protein/albumin ratio (CAR), and lymph node metastasis in patients with cN0 gastric cancer. To establish a nomogram model to predict the risk of lymph node metastasis in patients with cN0 gastric cancer. Methods: The preoperative systemic inflammatory markers and clinical data of 134 patients with cN0 gastric cancer were retrospectively analyzed, and these markers of patients with negative (pN0) or positive (pN+ ) lymph node metastasis in postoperative pathological diagnosis were compared. The receiver operating characteristic (ROC) curve was used to evaluate the predictive effect of preoperative systemic inflammatory markers on lymph node metastasis. The influencing factors for lymph node metastasis were assessed by univariate analysis and multivariate logistic regression analysis. A nomogram subsequently established by R software was validated by Bootstrap resampling as internal validation. Results: Compared with pN0 group, NE (P=0.022), CRP (P<0.001), NLR (P<0.001), PLR (P=0.003) and CAR (P<0.001) were higher, LY (P=0.003) and Alb (P=0.042) were lower in pN+ group. ROC curve analysis showed that the area under the curve (AUC) of postoperative pathological lymph node metastasis in patients with cN0 gastric cancer diagnosed by NLR, PLR and CAR were 0.687, 0.651 and 0.694, respectively, and the best cutoff values were 2.12, 113.59 and 0.02, respectively. The corresponding sensitivity and specificity were 62.9% and 72.2%, 77.4% and 48.6%, 74.2% and 58.3%, respectively. Univariate analysis showed that tumor size, depth of invasion, NLR, PLR and CAR were associated with lymph node metastasis in cN0 gastric cancer patients (all P<0.05). Multivariate analysis showed that depth of invasion, NLR and CAR were independent influencing factors of lymph node metastasis in patients with cN0 gastric cancer. OR were 8.084, 3.540 and 3.092, respectively (all P<0.05). The C-index of the nomogram model was 0.847 (95% CI: 0.782-0.915). The predicting calibration curve was properly fit with the ideal curve in calibration chart. Conclusion: Combination of NLR and CAR to establish a nomogram model has a good consistency and can accurately predict the risk of lymph node metastasis in patients with cN0 gastric cancer.