Development and validation of a nomogram for patients with stage II/III gastric adenocarcinoma after radical surgery - Wang, Lei; Han, Huiqiong; Feng, Liwen; Qin, Yanru (Frontiers in Surgery, 2022)
Background: We aimed to construct nomograms based on clinicopathological features and routine preoperative hematological indices to predict cancer-specific survival (CSS) and disease-free survival (DFS) in patients with stage II/III gastric adenocarcinoma (GA) after radical resection. Methods: We retrospectively analyzed 468 patients with stage II/III GA after curative gastrectomy between 2013 and 2018; 70% of the patients were randomly assigned to the training set (n=327) and the rest were assigned to the validation set (n=141). The nomogram was constructed from independent predictors derived from the Cox regression in the training set. Using the consistency index, the calibration and the time-dependent receiver operating characteristic curves were used to evaluate the accuracy of the nomogram. Decision curve analysis was used to assess the value of the model in clinical applications. Patients were further divided into low- and high-risk groups based on the nomogram risk score. Results: Multivariate Cox model identified depth of invasion, lymph node invasion, tumor differentiation, adjuvant chemotherapy, CA724, and platelet-albumin ratio as covariates associated with CSS and DFS. CA199 is a risk factor unique to CSS. The nomogram constructed using the results of the multivariate analysis showed high accuracy with a consistency index of 0.776 (CSS) and 0.770 (DFS). Moreover, the area under the curve values for the 3-and 5-year CSS were 0.875 and 0.926, and the corresponding values for DFS were 0.873 and 0.920, respectively. The nomogram had a greater clinical benefit than the TNM staging system. High-risk patients based on the nomogram had a worse prognosis than low-risk patients. Conclusion: The prognostic nomogram for patients with stage II/III GA after radical gastrectomy established in this study has a good predictive ability, which is helpful for doctors to accurately evaluate the prognosis of patients to make more reasonable treatment plans.