[1] Sung H, Ferlay J, Siegel R L, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[J]. CA Cancer J Clin, 2021,71(3):209-249.
[2] Zheng R, Zhang S, Zeng H, et al. Cancer incidence and mortality in China, 2016[J]. Journal of the National Cancer Center, 2022,2(1):1-9.
[3] Chen W, Xia C, Zheng R, et al. Disparities by province, age, and sex in site-specific cancer burden attributable to 23 potentially modifiable risk factors in China: a comparative risk assessment[J]. Lancet Glob Health, 2019,7(2):e257-e269.
[4] Tran K B, Lang J J, Compton K, et al. The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019[J]. The Lancet, 2022,400(10352):563-591.
[5] Kachuri L, Graff R E, Smith-Byrne K, et al. Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction[J]. Nat Commun, 2020,11(1):6084.
[6] He Y Q, Wang T M, Ji M, et al. A polygenic risk score for nasopharyngeal carcinoma shows potential for risk stratification and personalized screening[J]. Nat Commun, 2022,13(1):1966.
[7] Baker M, Cameron J M, Sala A, et al. Multicancer early detection with a spectroscopic liquid biopsy platform.[J]. Journal of Clinical Oncology, 2022,40(16_suppl):3034.
[8] In T V S, Arkani M, Post E, et al. Detection and localization of early- and late-stage cancers using platelet RNA[J]. Cancer Cell, 2022,40(9):999-1009.
[9] Gao Q, Wang C, Yang X, et al. 909P A multi-cancer early detection model based on liquid biopsy of multi-omics biomarkers: A proof of concept study (PROMISE study)[J]. Annals of Oncology, 2022,33:S963-S964.
[10] Mikhael P G, Wohlwend J, Yala A, et al. Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography[J]. J Clin Oncol, 2023,41(12):2191-2200.
[11] Yala A, Mikhael P G, Strand F, et al. Toward robust mammography-based models for breast cancer risk[J]. Sci Transl Med, 2021,13(578).
[12] Shen M, Zou Z, Bao H, et al. Cost-effectiveness of artificial intelligence-assisted liquid-based cytology testing for cervical cancer screening in China[J]. The Lancet, Regional Health - Western Pacific, 2023:100726.