A 10-year review of survival among patients with metastatic gastrointestinal cancers: a population-based study

Metastasis patterns and prognosis in young gastric cancer patients: A propensity score‑matched SEER database analysis

BACKGROUND

Whether young patients with metastatic gastric cancer (GC) had distinct metastasis patterns and survival outcomes from older patients remains controversial. The aim of the present study was to explore the metastasis patterns and prognostic factors in young patients and evaluate the survival outcome in comparison to their older counterparts.

MATERIALS AND METHODS

We identified patients with metastatic GC in the surveillance, epidemiology, and end results (SEER) database from 2010 to 2015. The patients were divided into two groups based on age at diagnosis: younger (≤40 years old) and older (>40 years old). We employed the chi-squared test to compare the clinicopathological characteristics between the two age groups. Furthermore, we conducted survival analyses using Kaplan-Meier and Cox regression analyses. To balance disparities in baseline characteristics, we employed propensity score matching (PSM).

RESULTS

We identified 5,580 metastatic GC patients from the SEER database, with 237 (4.2%) classified as younger and 5343 (95.8%) as older patients. A total of 237 pairs of patients were generated after adjustment by PSM. Patients in the younger group exhibited a higher proportion of bone-only metastases and a lower proportion of liver-only metastases compared with patients in the older group. Multivariate Cox regression analysis demonstrated that youth was an independent protective factor for overall survival (OS) before and after PSM, but not for gastric cancer-specific survival (GCSS). Among the younger group, patients with liver-only metastasis demonstrated the best prognosis, whereas patients with lung-only metastasis exhibited significantly worse survival outcomes compared with liver-only metastases, even comparable to that of bone metastasis.

CONCLUSIONS

Compared with the older group, the metastatic GC patients in the younger group exhibited more aggressive tumors but better prognoses. The metastasis pattern and its effect on the prognosis of GC varied by age group.

The incidence, risk factors and predictive nomograms for early death among patients with stage IV gastric cancer: a population-based study

Background

Although advances in the treatment of stage IV gastric cancer (GC) patients, some patients were observed to die within 3 months of initial diagnosis. The present study aimed to explore the early mortality and risk factors for stage IV GC and further develop nomograms.

Methods

A total of 2,174 eligible stage IV GC patients were selected from the Surveillance, Epidemiology, and End Results database. Logistic regression analyses were used to determine the risk factors and develop the nomograms to predict all-cause early death and cancer-specific early death. The predictive performance of the nomograms was assessed by receiver operating characteristic curves (ROC), calibration plots and decision curve analyses (DCA) in both training and validation cohorts.

Results

Of 2,174 patients enrolled, 708 died within 3 months of initial diagnosis (n=668 for cancer-specific early death). Early mortality remained stable from 2010-2015. Non-Asian or Pacific Islander (API) race, poorer differentiation, middle sites of the stomach, no surgery, no radiotherapy, no chemotherapy, lung metastases and liver metastases were associated with high risk of both all-causes early death and cancer-specific early death. The nomograms constructed based on these factors showed favorable sensitivity, with the area under the ROC range of 0.816-0.847. The calibration curves and DCAs also exhibited adequate fit and ideal net benefit in prediction and clinical application.

Conclusions

Approximately one-third of stage IV GC patients experienced early death. These associated risk factors and predictive nomograms may help clinicians identify the patients at high risk of early death and be the reference for treatment choices.