3.3. Developing and validating the nomogram
REGRESSION
A nomogram was constructed based on independent prognostic factors derived from multivariate Cox regression analysis to predict the OS at 6, 12, and 24 months in patients with metastatic gastric adenocarcinoma. As shown in Figure Nomogram for predicting 6-, 12-, and 24-month OS of patients with metastatic gastric adenocarcinoma. For each patient, 9 lines are drawn up to determine the points received from the predictors in the line plot. The sum of these points is on the Total Points axis. In addition, 3 lines are drawn down to determine the possibility of 6, 12, and 24 months. OS = overall survival.ROC curves of the nomogram in the prediction of prognosis. 6-month OS (A) and 12-month OS (B) and 24-month OS (C) in the training set; 6-month OS (D) and 12-month OS (E) and 24-month OS (F) in validation set. ROC = receiver operating characteristic curve, AUC = areas under the curve, OS = overall survival.Calibration plots of OS nomogram model. 6-month calibration plot of OS using training set (A); 12-month calibration plot of OS using training set (B); 24-month calibration plot of OS using training set (C);6-month calibration plot of OS using validation set (D);12-month calibration plot of OS using validation set (E);24-month calibration plot of OS using validation set (F). OS = overall survival.Decision curve analysis for the nomogram in the prediction of prognosis of patients with metastatic gastric adenocarcinoma. The Decision curve analysis of the training set (A) and validation set (B). The x-axis shows the threshold probabilities, and the y-axis measures the net benefit calculated by adding the true positives and subtracting the false positives.Kaplan–Meier curves of overall survival (OS) for patients in different risk levels. The survival of the low- and high-risk groups in the training set (A), validation set(B).