ZHANG Haibao 1 , WANG Chaoyang 1 , LIN Hao 1 , JU Jiahua 1 , YANG Xiongfei 2 , YANG Weilin 3 , YU Yongjian 1,3
  • 1. The First Clinical Medical College, Lanzhou University, Lanzhou 730000, P. R. China;
  • 2. Department of Anorectal Surgery, Gansu Provincial People’s Hospital, Lanzhou 730000, P. R. China;
  • 3. Department of Gastrointestinal Surgery / Hernia and Abdominal Wall Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, P. R. China;
YU Yongjian, Email: ylongy@163.com
gastrointestinal stromal tumor; nomogram; predictive model; survival analysis
10.7507/1007-9424.202311053
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Objective To analyze and identify the relevant risk factors affecting postoperative relapse-free survival in the primary gastrointestinal stromal tumors (GIST) and develop a nomogram predictive model for relapse-free survival (RFS) for postoperative GIST patients. Methods A retrospective cohort study was conducted, collecting clinical data of 454 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. The data was randomly divided into a training group (n=317) and a validation group (n=137) at a ratio of 7:3 using R software functions. Single-factor and multiple-factor COX regression analyses were used to determine independent risk factors affecting postoperative RFS in GIST. Nomogram models predicting 3-year and 5-year RFS were constructed. Model performance was evaluated using the C-index, calibration curve, and receiver operating characteristic (ROC) curve. Clinical utility was compared with the Modified National Institutes of Health (M-NIH) grading standard through decision curve analysis (DCA). Results Single-factor analysis showed that blood type, tumor location, tumor size, differentiation degree, AJCC stage, histological type, mitotic rate, Ki-67 index, CD34, risk grading, FIB, PLR, perioperative transfusion, surgical method, lymph node detection, and targeted drug treatment time were related to postoperative RFS in GIST patients (P<0.05). Multiple-factor COX regression analysis revealed that tumor location, tumor size, differentiation degree, AJCC stage, mitotic rate, CD34, surgical method, lymph node detection, and targeted drug treatment time were independent risk factors affecting RFS in GIST patients (P<0.05). A nomogram predicting model was constructed based on these risk factors. The C-index of the training group and validation group were 0.685 (95% CI: 0.647-0.722) and 0.731 (95% CI: 0.679-0.783), respectively. ROC curve and calibration curve both demonstrated good predictive ability of the nomogram model, and DCA showed that the clinical utility of the nomogram model was superior to the M-NIH grading standard. Conclusions The results of this study suggest that in clinical practice, patients with GIST located in 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 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.