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Randomized Controlled Trial
. 2023 Mar 3;102(9):e33019.
doi: 10.1097/MD.0000000000033019.

Development and validation of prognostic nomogram for patients with metastatic gastric adenocarcinoma based on the SEER database

Xianming Liu  1 , Yanyan Ren  1 , Fayan Wang  1 , Yuqing Bu  2 , Lili Peng  2 , Jinlong Liang  1 , Xiyun Kang  1 , Hongzhen Zhang  2
Affiliations
Randomized Controlled Trial

Development and validation of prognostic nomogram for patients with metastatic gastric adenocarcinoma based on the SEER database

Xianming Liu et al. Medicine (Baltimore). .

Abstract

The aim of this study was to investigate the prognostic factors affecting overall survival in patients with metastatic gastric adenocarcinoma and to establish a nomogram prediction model for comprehensive clinical application. Data from 2370 patients with metastatic gastric adenocarcinoma between 2010 and 2017 were retrieved from the surveillance, epidemiology, and end results database. They were randomly divided into a training set (70%) and a validation set (30%), univariate and multivariate Cox proportional hazards regressions were used to screen important variables that may affect overall survival and to establish the nomogram. The nomogram model was evaluated using a receiver operating characteristic curve, calibration plot, and decision curve analysis. Internal validation was performed to test the accuracy and validity of the nomogram. Univariate and multivariate Cox regression analyses revealed that, age, primary site, grade, and American joint committee on cancer. T, bone metastasis, liver metastasis, lung metastasis, tumor Size, and chemotherapy were identified as independent prognostic factors for overall survival and were included in the prognostic model to construct a nomogram. The prognostic nomogram showed good overall survival risk stratification ability for the area under the curve, calibration plots, and decision curve analysis in both the training and validation sets. Kaplan-Meier curves further showed that patients in the low-risk group had better overall survival. This study synthesizes the clinical, pathological, therapeutic characteristics of patients with metastatic gastric adenocarcinoma, establishes a clinically effective prognostic model, and that can help clinicians to better evaluate the patient's condition and provide accurate treatment.

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Conflict of interest statement

The authors have no conflicts of interest to disclose.

Figures

Figure 1.
Figure 1.
The inclusion criteria flowchart of recruited patients in SEER database. SEER = surveillance, epidemiology, and end results database.
Figure 2.
Figure 2.
The X-tile analysis of best-cutoff points of age and tumor size variables. (A) X-tile plot of training sets in age; (B) the cutoff point was highlighted using a histogram of the entire cohort; (C) the distinct prognosis determined by the cutoff point was shown using a Kaplan–Meier plot (low subset = blue, middle subset = gray, high subset = magenta); (D) X-tile plot of training sets in tumor size; (E) the cutoff point was highlighted using a histogram; (F) Kaplan–Meier plot of prognosis determined by the cutoff point (low subset = blue, middle subset = gray, high subset = magenta).
Figure 3.
Figure 3.
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.
Figure 4.
Figure 4.
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.
Figure 5.
Figure 5.
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.
Figure 6.
Figure 6.
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.
Figure 7.
Figure 7.
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).
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