Risk scoring system combined with traditional Chinese medicine constitution identification improves colorectal advanced neoplasms screening effectiveness for early colonoscopy
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND The Asia-Pacific Colorectal Screening (APCS) score was designed with the purpose of distinguishing individuals at high risk (HR) for colorectal advanced neoplasia (AN). Traditional Chinese medicine (TCM) constitution was also linked with colorectal cancer (CRC). AIM To integrate the APCS score with TCM constitution identification as a new algorithm to screen for CRC. METHODS A cross-sectional multicenter study was carried out in three hospitals, enrolling 1430 patients who were asymptomatic and undergoing screening colonoscopy from 2022 to 2023. Patients were considered to have average risk, moderate risk, or HR with their APCS score. Odd ratios assessed the relationship between TCM constitution and disease progression. A TCM constitution risk score was created. The sensitivity and specificity of the new algorithm were calculated to evaluate diagnostic performance in detecting advanced adenoma (AA), CRC, and AN. RESULTS Of the 1430 patients, 370 (25.9%) were categorized as average risk, 755 (52.8%) as moderate risk, and 305 (21.3%) as HR. Using the combined APCS score and the TCM constitution (damp-heat, qi-deficiency, yang-deficiency, phlegm-dampness, and inherited special constitution as positive) algorithm, 72.2% of patients with AA and 73.7% of patients with AN were detected. Compared with the APCS score alone, the new algorithm significantly improved the sensitivity for screening AA [72.2%, 95% confidence interval (CI): 64.4%-80.0% vs 49.2%, 95%CI: 40.5%-57.9%] and AN (73.7%, 95%CI: 66.4%-81.1% vs 51.1%, 95%CI: 42.7%-59.5%). CONCLUSION The combination of APCS and TCM constitution identification questionnaires was valuable in identifying Chinese individuals who were asymptomatic for colorectal screening prioritization.
Authors: Qing-Hua Liu, Yue Hou, Shu Li, Yun-Long Gu, Chen-Xi Huang, Qian Kang, Ya-Jing Fan, Ling-Qin Zhu, Li Sun, Rui-Cheng Men, Xiao-Yan Li, Hui Wang, Xiu-Ying Wei, Zhao-Gang Sun, Yu-Qi He
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4415210700
