| Objective To identify patients with gastric multiple primary cancer based on a retrospective analysis of the SEER database in the United States, and to evaluate their clinical characteristics, prognostic assessment and compare the performance of different machine learning models. Methods Clinical data of patients with gastric cancer diagnosed between 2000 and 2022 were collected. Overall survival was estimated using the Kaplan–Meier method. The Log-rank test was used for comparison between groups. Propensity score matching (PSM) at a 1∶1 ratio was performed to adjust for confounding factors, and survival differences between the gastric cancer-only group and the gastric multiple primary cancer group were compared before and after PSM. The Cox proportional hazards regression model was used to identify prognostic factors in patients with gastric multiple primary cancer. Data were randomly divided into training and validation sets at a 7∶3 ratio. The Cox model, random survival forest (RF) model, and survival tree (ST) model were used to predict survival, and model performance was evaluated. Results A total of 53,752 patients with gastric cancer were included, among whom 4,174 had developed a second primary cancer(SPC). The median age at diagnosis for gastric cancer and SPC was 68 years and 71 years, respectively. Synchronous and metachronous SPC occurred in 1,190 and 2,984 patients, with median time latency of 1 month and 45 months, respectively. Colorectal cancer and lung cancer were the most common SPC types. Multivariate Cox analysis showed that male, poor differentiation, elderly age, advanced stage, adenocarcinoma, history of surgery, latency between the two cancers, type of SPC, household income and patient geographic region were independent prognostic factors for patients with gastric multiple primary cancer (P<0.05). Time-dependent ROC curves showed that the area under the curve (AUC) for 1?year, 3?year, and 5?year survival were 0.899, 0.765, and 0.739, respectively. Comparison of the three prognostic models indicated that the Cox and random survival forest models outperformed the survival tree model. Conclusion Male, elderly age, advanced stage, latency between two cancers, SPC type, family income and the patients located regions are independent prognostic factors for patients with multiple primary gastric cancers. The survival prediction model established has a good effect and can provide data support for clinicians to improve the early identification and diagnosis and treatment of patients with multiple primary gastric cancers. |
