Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
Cancer Lett. 2024 Aug 10;597:217057. doi: 10.1016/j.canlet.2024.217057. Epub 2024 Jun 12.
Risk prediction tools for colorectal cancer (CRC) have potential to improve the efficiency of population-based screening by facilitating risk-adapted strategies. However, such an applicable tool has yet to be established in the Chinese population. In this study, a risk score was created using data from the China Kadoorie Biobank (CKB), a nationwide cohort study of 409,854 eligible participants. Diagnostic performance of the risk score was evaluated in an independent CRC screening programme, which included 91,575 participants who accepted colonoscopy at designed hospitals in Zhejiang Province, China. Over a median follow-up of 11.1 years, 3136 CRC cases were documented in the CKB. A risk score was created based on nine questionnaire-derived variables, showing moderate discrimination for 10-year CRC risk (C-statistic = 0.68, 95 % CI: 0.67-0.69). In the CRC screening programme, the detection rates of CRC were 0.25 %, 0.82 %, and 1.93 % in low-risk (score <6), intermediate-risk (score: 6-19), and high-risk (score >19) groups, respectively. The newly developed score exhibited a C-statistic of 0.65 (95 % CI: 0.63-0.66), surpassing the widely adopted tools such as the Asia-Pacific Colorectal Screening (APCS), modified APCS, and Korean Colorectal Screening scores (all C-statistics = 0.60). In conclusion, we developed a novel risk prediction tool that is useful to identify individuals at high risk of CRC. A user-friendly online calculator was also constructed to encourage broader adoption of the tool.
结直肠癌(CRC)风险预测工具通过促进风险适应策略,有可能提高基于人群的筛查效率。然而,在中国人群中尚未建立这样一个适用的工具。在这项研究中,使用来自中国慢性病前瞻性研究(CKB)的数据创建了一个风险评分,该研究是一项针对 409854 名合格参与者的全国性队列研究。风险评分的诊断性能在中国浙江省的一个独立 CRC 筛查项目中进行了评估,该项目纳入了 91575 名接受结肠镜检查的参与者。在中位随访 11.1 年期间,CKB 记录了 3136 例 CRC 病例。基于九个问卷调查衍生变量创建了一个风险评分,对 10 年 CRC 风险的区分度为中等(C 统计量为 0.68,95%置信区间:0.67-0.69)。在 CRC 筛查项目中,CRC 的检出率在低风险(评分<6)、中风险(评分:6-19)和高风险(评分>19)组中分别为 0.25%、0.82%和 1.93%。新开发的评分的 C 统计量为 0.65(95%置信区间:0.63-0.66),超过了广泛应用的工具,如亚太结直肠癌筛查(APCS)、改良 APCS 和韩国结直肠癌筛查评分(所有 C 统计量均为 0.60)。总之,我们开发了一种新的风险预测工具,可用于识别 CRC 高危个体。还构建了一个用户友好的在线计算器,以鼓励更广泛地采用该工具。