ObjectiveTo analyze the relevant risk factors affecting postoperative relapse-free survival (RFS) in the primary gastrointestinal stromal tumors (GIST) and develop a Nomogram predictive model of postoperative RFS for the GIST patients. MethodsThe patients diagnosed with GIST by postoperative pathology from January 2011 to December 2020 at the First Hospital of Lanzhou University and Gansu Provincial People’s Hospital were collected, and then were randomly divided into a training set and a validation set at a ratio of 7∶3 using R software function. The univariate and multivariate Cox regression analysis were used to identify the risk factors affecting the RFS for the GIST patients after surgery, and then based on this, the Nomogram predictive model was constructed to predict the probability of RFS at 3- and 5-year after surgery for the patients with GIST. The effectiveness of the Nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), consistency index (C-index), and calibration curve, and the clinical utility of the Nomogram and the modified National Institutes of Health (M-NIH) classification standard was evaluated using the decision curve analysis (DCA). ResultsA total of 454 patients were included, including 317 in the training set and 137 in the validation set. The results of multivariate Cox regression analysis showed that the tumor location, tumor size, differentiation degree, American Joint Committee onCancer TNM stage, mitotic rate, CD34 expression, treatment method, number of lymph node detection, and targeted drug treatment time were the influencing factors of postoperative RFS for the GIST patients (P<0.05). The Nomogram predictive model was constructed based on the influencing factors. The C-index of the Nomogram in the training set and validation set were 0.731 [95%CI (0.679, 0.783)] and 0.685 [95%CI (0.647, 0.722)], respectively. The AUC (95%CI) of distinguishing the RFS at 3- and 5-year after surgery were 0.764 (0.681, 0.846) and 0.724 (0.661, 0.787) in the training set and 0.749 (0.625, 0.872) and 0.739 (0.647, 0.832) in the validation set, respectively. The calibration curve results showed that a good consistency of the 3-year and 5-year recurrence free survival rates between the predicted results and the actual results in the training set, while which was slightly poor in the validation set. There was a higher net benefit for the 3-year recurrence free survival rate after GIST surgery when the threshold probability range was 0.19 to 0.57. When the threshold probability range was 0.44 to 0.83, there was a higher net benefit for the 5-year recurrence free survival rate after GIST surgery. And within the threshold probability ranges, the net benefit of the Nomogram was better than the M-NIH classification system at the corresponding threshold probability. ConclusionsThe results of this study suggest that the patients with GIST located in the other sites (mainly including the esophagus, duodenum, and retroperitoneum), with tumor size greater than 5 cm, poor or undifferentiated differentiation, mitotic rate lower than 5/50 HPF, negative CD34 expression, ablation treatment, number of lymph nodes detected more than 4, and targeted drug treatment time less than 3 months need to closely pay attentions to the postoperative recurrence. The discrimination and clinical applicability of the Nomogram predictive model are good.