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- Title
Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies.
- Authors
Tian, Jianbo; Zhang, Ming; Zhang, Fuwei; Gao, Kai; Lu, Zequn; Cai, Yimin; Chen, Can; Ning, Caibo; Li, Yanmin; Qian, Sangni; Bai, Hao; Liu, Yizhuo; Zhang, Heng; Chen, Shuoni; Li, Xiangpan; Wei, Yongchang; Li, Bin; Zhu, Ying; Yang, Jinhua; Jin, Mingjuan
- Abstract
Background: Early detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population. Methods: To develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants. Results: Three trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS183 demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose–response effect of PRS183 on incident colorectal neoplasms. Incorporating PRS183 with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32). Conclusions: Our comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity.
- Subjects
ZHEJIANG Sheng (China); UNITED Kingdom; EARLY detection of cancer; ADENOMATOUS polyps; COLORECTAL cancer; LUNGS; RACIAL inequality; GENETIC risk score; HEALTH equity; CANCER hospitals
- Publication
Genome Medicine, 2024, Vol 16, Issue 1, p1
- ISSN
1756-994X
- Publication type
Article
- DOI
10.1186/s13073-024-01355-y