Predicting the prognosis of small intestinal stromal tumors in the post-imatinib era: a study based on the SEER...

The prognosis of small intestinal stromal tumors (SISTs) in the post-imatinib era is influenced by a complex interplay of clinicopathological factors. This study aimed to develop and validate predictive models for overall survival (OS) and cancer-specific survival (CSS) in patients with SISTs using data from the Surveillance, Epidemiology, and End Results (SEER) database.

We retrospectively analyzed 3,504 patients diagnosed with SISTs between 2012 and 2023. Patients were randomly divided into a training cohort (n=2,453) and a testing cohort (n=1,051). Cox proportional hazards regression analyses were performed in the training cohort to identify independent prognostic factors for OS and CSS. Significant predictors were used to construct nomograms for predicting 1-, 3-, and 5-year survival probabilities. The models' performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA) in both the training and testing cohorts.

Multivariate Cox regression analysis identified age ≥65 years, male sex, high tumor grade (III/IV), distant metastasis (M1), no surgery, unmarried status, and no chemotherapy as independent risk factors for worse OS (all P<0.01). For CSS, independent risk factors included age ≥65 years, high tumor grade (III/IV), lymph node metastasis (N1), distant metastasis (M1), and no surgery (all P<0.05). These factors were incorporated into the nomograms, which demonstrated satisfactory predictive accuracy. In the testing cohort, the area under the curve (AUC) for the OS nomogram at 1, 3, and 5 years were 0.763, 0.728, and 0.758, and for the CSS nomogram were 0.763, 0.784, and 0.801. Calibration curves showed good agreement between predicted and observed survival, and DCA confirmed the clinical utility of the nomograms.

We developed and validated promising nomograms for predicting OS and CSS in patients with SISTs. These models, incorporating readily available clinicopathological factors, may serve as a supplementary tool for individualized risk stratification and clinical decision-making in the post-imatinib era.