Abstract
BACKGROUND: Preoperative imaging examination is the primary method for diagnosing metastatic gastrointestinal stromal tumor (GIST), but it is associated with a high rate of missed diagnosis. Therefore, it is important to establish an accurate model for predicting occult peritoneal metastasis (PM) of GIST. PATIENTS AND METHODS: GIST patients seen between April 2002 and December 2018 were selected from an institutional database. Using multivariate logistic regression analyses, we created a nomogram to predict occult PM of GIST and validated it with an independent cohort from the same center. The concordance index (C-index), decision curve analysis (DCA) and a clinical impact curve (CIC) were used to evaluate its predictive ability. RESULTS: A total of 522 eligible GIST patients were enrolled in this study and divided into training (n=350) and validation cohorts (n=172). Factors associated with occult PM were included in the model: tumor size (odds ratio [OR] 1.194 95% confidence interval [CI], 1.034-1.378; p=0.016), primary location (OR 7.365 95% CI, 2.192-24.746; p=0.001), tumor capsule (OR 4.282 95% CI, 1.209-15.166; p=0.024), Alb (OR 0.813 95% CI, 0.693-0.954; p=0.011) and FIB (OR 2.322 95% CI, 1.410-3.823; p=0.001). The C-index was 0.951 (95% CI, 0.917-0.985) in the training cohort and 0.946 (95% CI, 0.900-0.992) in the validation cohort. In the training cohort, the prediction model had a sensitivity of 82.8%, a specificity of 93.8%, a positive predictive value of 54.7%, and a negative predictive value of 98.4%; the validation cohort values were 94.7%, 85.0%, 43.9% and 99.2%, respectively. DCA and CIC results showed that the nomogram had clinical value in predicting occult PM in GIST patients. CONCLUSION: Imaging and inflammatory indexes are significantly associated with microscopic metastases of GIST. A nomogram including these factors would have an excellent ability to predict occult PM.