FIT-based risk-stratification model effectively screens colorectal neoplasia and early-onset colorectal cancer in Chinese population: a nationwide multicenter prospective study

基于粪便免疫化学检测(FIT)的风险分层模型可有效筛查中国人群中的结直肠肿瘤和早发性结直肠癌:一项全国多中心前瞻性研究

阅读:1

Abstract

No fully validated risk-stratification strategies have been established in China where colonoscopies resources are limited. We aimed to develop and validate a fecal immunochemical test (FIT)-based risk-stratification model for colorectal neoplasia (CN); 10,164 individuals were recruited from 175 centers nationwide and were randomly allocated to the derivation (n = 6776) or validation cohort (n = 3388). Multivariate logistic analyses were performed to develop the National Colorectal Polyp Care (NCPC) score, which formed the risk-stratification model along with FIT. The NCPC score was developed from eight independent predicting factors and divided into three levels: low risk (LR 0-14), intermediate risk (IR 15-17), and high risk (HR 18-28). Individuals with IR or HR of NCPC score or FIT+ were classified as increased-risk individuals in the risk-stratification model and were recommended for colonoscopy. The IR/HR of NCPC score showed a higher prevalence of CNs (21.8%/32.8% vs. 11.0%, P < 0.001) and ACNs (4.3%/9.2% vs. 2.0%, P < 0.001) than LR, which was also confirmed in the validation cohort. Similar relative risks and predictive performances were demonstrated between non-specific gastrointestinal symptoms (NSGS) and asymptomatic cohort. The risk-stratification model identified 73.5% CN, 82.6% ACN, and 93.6% CRC when guiding 52.7% individuals to receive colonoscopy and identified 55.8% early-onset ACNs and 72.7% early-onset CRCs with only 25.6% young individuals receiving colonoscopy. The risk-stratification model showed a good risk-stratification ability for CN and early-onset CRCs in Chinese population, including individuals with NSGS and young age.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。