Establishment and validation of a prognostic nomogram for extra-gastrointestinal stromal tumors.

BACKGROUND

Extra-gastrointestinal stromal tumor (EGIST) is a rare subtype of gastrointestinal stromal tumor, with limited information on its clinical characteristics and prognostic factors. This study aims to identify the risk factors affecting survival in EGIST patients and to develop a prognostic nomogram for predicting EGIST-specific survival (TSS).

METHODS

Patients diagnosed with EGIST, aged 18 to 80, were enrolled from the Surveillance, Epidemiology, and End Results (SEER) Research Plus database, covering the years 2000 to 2019. Univariate and multivariate analyses were conducted to identify risk factors for developing a nomogram. The predictive accuracy of the nomogram was evaluated using time-dependent receiver operating characteristic curves, calibration plots, and the concordance index. Decision curve analysis (DCA) was performed to assess the nomogram's clinical utility and net benefit for application in clinical practice. Additionally, the nomogram's performance was compared with the tumor SEER stage.

RESULTS

A total of 389 patients were included in this study. Univariate and multivariate analyses identified age, household income, surgery, tumor grade, tumor size, and tumor SEER stage as significant predictors of TSS (all P<0.05). These factors were incorporated into the prognostic nomogram. The nomogram demonstrated superior prognostic value compared to the tumor SEER stage alone, as evidenced by the area under the curve and concordance index. The calibration plot indicated a high level of accuracy in forecasting survival probabilities. Furthermore, DCA highlighted the nomogram's clinical applicability and positive net benefit. The nomogram also proved more effective than the tumor SEER stage alone in identifying patients with poorer prognoses.

CONCLUSIONS

Age, household income, surgery, tumor grade, tumor size, and tumor SEER stage were identified as risk factors for TSS in patients with EGIST. We have developed and validated a prognostic nomogram to predict TSS in EGIST patients, which may improve patient management and guide personalized medical treatment for EGIST.