Additional file 1 of Development, validation, and evaluation of a risk assessment tool for personalized screening of gastric cancer in Chinese populations
Creators: name: Zhu, Xia
name: Lv, Jun
name: Zhu, Meng
name: Yan, Caiwang
name: Deng, Bin
name: Yu, Canqing
name: Guo, Yu
name: Ni, Jing
name: She, Qiang
name: Wang, Tianpei
name: Wang, Jiayu
name: Jiang, Yue
name: Chen, Jiaping
name: Hang, Dong
name: Song, Ci
name: Gao, Xuefeng
name: Wu, Jian
name: Dai, Juncheng
name: Ma, Hongxia
name: Yang, Ling
name: Chen, Yiping
name: Song, Mingyang
name: Wei, Qingyi
name: Chen, Zhengming
name: Hu, Zhibin
name: Shen, Hongbing
name: Ding, Yanbing
name: Li, Liming
name: Jin, Guangfu
Publisher: name: figshare
Year: 2023
Subjects: subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Biotechnology
subject: Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Cancer

description: Additional file 1: Appendix 1.0. Study design and subjects. Appendix 2.0. Assessment of risk factors. Appendix 3.0. Definition of GC cases. Table S1. Results of univariate Cox regression analysis in the CKB cohort. Table S2. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 1: excluding weak variables in the simplified model. Table S3. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 2: integrating lifestyle factors as an index. Table S4. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 3: excluding participants who had GC diagnosis within the first year after recruitment. Table S5. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 4: excluding participants who had cancer at baseline. Table S6. Results and corresponding risk points in sensitivity analysis 5: competing risk model by considering death as a competing event. Table S7. Risk categories by deciles of the GCRS in the CKB cohort. Table S8. Internal validation of the GCRS in different regions of CKB. Table S9. Harrell’s C-index of the GCRS from ten-fold cross validation in the CKB cohort. Table S10. Risk categories of the GCRS in the Changzhou cohort. Table S11. Risk categories and associated 3-year, 5-year, and 10-year risk of incident GC derived from CKB. Table S12. Risk categories of different gastric lesions in the Yangzhou screening program. Table S13. Performance of the GCRS across different predicted risk cutoffs in the Yangzhou screening program. Table S14. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 1: excluding weak variables in the simplified model. Table S15. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 2: integrating lifestyle factors as an index. Table S16. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 3: excluding participants who had GC diagnosis within the first year after recruitment. Table S17. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 4: excluding participants who had cancer at baseline. Table S18. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 5: competing risk model. Table S19. The GCRS and corresponding 3-year, 5-year, and 10-year risk of incident GC derived from the CKB cohort. Fig. S1. Study design and eligible participants’ selection procedures in three studies. Fig. S2. The relationship of the GCRS with incident GC risk in the CKB cohort. Fig. S3. The relationship of the GCRS with incident GC risk in the Changzhou cohort. Fig. S4. Calibration and discrimination of the GCRS in sensitivity analysis 1: excluding weak variables in the simplified model. Fig. S5. Calibration and discrimination of the GCRS in sensitivity analysis 2: integrating lifestyle factors as an index. Fig. S6. Calibration and discrimination of the GCRS in sensitivity analysis 3: excluding participants who had GC diagnosis within the first year after recruitment. Fig. S7. Calibration and discrimination of the GCRS in sensitivity analysis 4: excluding participants who had cancer at baseline. Fig. S8. Calibration and discrimination of the GCRS in sensitivity analysis 5: competing risk model.