Xiaoqian Zhang1,2, Liang Ning2, Yulong Hu2, Shanfeng Zhao2, Zequn Li2, Leping Li3, Yong Dai4, Lixin Jiang5, Ailiang Wang6, Xianqun Chu7, Yuming Li8, Daogui Yang9, Chunlei Lu10, Linguo Yao11, Gang Cui12, Huizhong Lin13, Gang Chen14, Qing Cui15, Hongliang Guo16, Huanhu Zhang17, Zengjun Lun18, Lijian Xia19, Yingfeng Su20, Guoxin Han21, Xizeng Hui22, Zhixin Wei23, Zuocheng Sun24, Shuai Shen2, Yanbing Zhou25. 1. Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China. 2. Department of General Surgery, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. 3. Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong, China. 4. Department of General Surgery, Qilu Hospital of Shandong University, Jinan, China. 5. Department of Gastrointestinal Thyroid Surgery, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China. 6. Department of Gastrointestinal Surgery, Affiliated Hospital of Jining Medical University, Jining, Shandong, China. 7. Department of Gastroenterology Surgery, Jining No.1 People's Hospital, Jining, Shandong, China. 8. Department of Gastrointestinal Surgery, Binzhou Medical University Hospital, Binzhou, Shandong, China. 9. Department of Gastrointestinal Surgery, Liaocheng People's Hospital, Liaocheng, Shandong, China. 10. Department of Laparoscopic Surgery Center, Linyi People's Hospital, Linyi, Shandong, China. 11. Department of Gastrointestinal Surgery, Shengli Oilfield Central Hospital, Yantai, Shandong, China. 12. Department of General Surgery, Taian City Central Hospital, Taian, Shandong, China. 13. Department of Gastric Surgery, Qingdao Municipal Hospital, Qingdao, Shandong, China. 14. Department of Gastrointestinal Surgery, Tengzhou Central People's Hospital, Tengzhou, Shandong, China. 15. Department of General Surgery, Zibo Central Hospital, Zibo, Shandong, China. 16. The Fourth Department of General Surgery, Shandong Cancer Hospital, Jinan, Shandong, China. 17. Department of General Surgery, Weihai Municipal Hospital, Weihai, Shandong, China. 18. Department of General Surgery, Zaozhuang Municipal Hospital, Zaozhuang, Shandong, China. 19. Department of Gastrointestinal Surgery, Shandong Province Qianfoshan Hospital, Jinan, Shandong, China. 20. Department of General Surgery, Dezhou People's Hospital, Dezhou, Shandong, China. 21. Department of General Surgery, Affiliated Hospital of Taishan Medical University, Taian, Shandong, China. 22. Department of Surgery, People's Hospital of Rizhao, Rizhao, Shandong, China. 23. Department of General Surgery, Heze Municipal Hospital, Heze, Shandong, China. 24. Department of Surgery, Weifang People's Hospital, Weifang, Shandong, China. 25. Department of General Surgery, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. zhouyanbing999@aliyun.com.
Abstract
BACKGROUND: Most previous risk-prediction models for gastrointestinal stromal tumors (GISTs) were based on Western populations. In the current study, we collected data from 23 hospitals in Shandong Province, China, and used the data to examine prognostic factors in Chinese patients and establish a new recurrence-free survival (RFS) prediction model. METHODS: Records were analyzed for 5285 GIST patients. Independent prognostic factors were identified using Cox models. Receiver operating characteristic curve analysis was used to compare a novel RFS prediction model with current risk-prediction models. RESULTS: Overall, 4216 patients met the inclusion criteria and 3363 completed follow-up. One-, 3-, and 5-year RFS was 94.6% (95% confidence interval [CI] 93.8-95.4), 85.9% (95% CI 84.7-87.1), and 78.8% (95% CI 77.0-80.6), respectively. Sex, tumor location, size, mitotic count, and rupture were independent prognostic factors. A new prognostic index (PI) was developed: PI = 0.000 (if female) + 0.270 (if male) + 0.000 (if gastric GIST) + 0.350 (if non-gastric GIST) + 0.000 (if no tumor rupture) + 1.259 (if tumor rupture) + 0.000 (tumor mitotic count < 6 per 50 high-power fields [HPFs]) + 1.442 (tumor mitotic count between 6 and 10 per 50 HPFs) + 2.026 (tumor mitotic count > 10 per 50 HPFs) + 0.096 × tumor size (cm). Model-predicted 1-, 3-, and 5-year RFS was S(12, X) = 0.9926exp(PI), S(36, X) = 0.9739exp(PI) and S(60, X) = 0.9471exp(PI), respectively. CONCLUSIONS: Sex, tumor location, size, mitotic count, and rupture were independently prognostic for GIST recurrence. Our RFS prediction model is effective for Chinese GIST patients.
BACKGROUND: Most previous risk-prediction models for gastrointestinal stromal tumors (GISTs) were based on Western populations. In the current study, we collected data from 23 hospitals in Shandong Province, China, and used the data to examine prognostic factors in Chinese patients and establish a new recurrence-free survival (RFS) prediction model. METHODS: Records were analyzed for 5285 GIST patients. Independent prognostic factors were identified using Cox models. Receiver operating characteristic curve analysis was used to compare a novel RFS prediction model with current risk-prediction models. RESULTS: Overall, 4216 patients met the inclusion criteria and 3363 completed follow-up. One-, 3-, and 5-year RFS was 94.6% (95% confidence interval [CI] 93.8-95.4), 85.9% (95% CI 84.7-87.1), and 78.8% (95% CI 77.0-80.6), respectively. Sex, tumor location, size, mitotic count, and rupture were independent prognostic factors. A new prognostic index (PI) was developed: PI = 0.000 (if female) + 0.270 (if male) + 0.000 (if gastric GIST) + 0.350 (if non-gastric GIST) + 0.000 (if no tumor rupture) + 1.259 (if tumor rupture) + 0.000 (tumor mitotic count < 6 per 50 high-power fields [HPFs]) + 1.442 (tumor mitotic count between 6 and 10 per 50 HPFs) + 2.026 (tumor mitotic count > 10 per 50 HPFs) + 0.096 × tumor size (cm). Model-predicted 1-, 3-, and 5-year RFS was S(12, X) = 0.9926exp(PI), S(36, X) = 0.9739exp(PI) and S(60, X) = 0.9471exp(PI), respectively. CONCLUSIONS: Sex, tumor location, size, mitotic count, and rupture were independently prognostic for GIST recurrence. Our RFS prediction model is effective for Chinese GIST patients.