ArticleCancer medicine2022
Improved risk scoring systems for colorectal cancer screening in Shanghai, China.
Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 19 citations in OpenAlex.
- Colonoscopy outcomes of primary screening negative participants highlight the missed diagnosis problem of colorectal cancer screening: an observational study from Yuexiu district in Guangzhou, China.Frontiers in oncology · 2025Article
- Cost-effectiveness of colorectal cancer screening under different scenarios of colonoscopy adherence: a microsimulation study.BMJ public health · 2025Article
- Age- and sex-stratified detection rates and associated factors of colorectal neoplasia in the Tianjin colorectal cancer screening program from 2012 to 2020.BMC gastroenterology · 2023Article
- Modifiable Risk Factors in High-Risk Groups of Colorectal Cancer Screening: A Cross-Sectional Study with Propensity Score Method.Risk management and healthcare policy · 2023Article
- A risk scoring system for advanced colorectal neoplasia in high-risk participants to improve current colorectal cancer screening in Tianjin, China.BMC gastroenterology · 2022Article
- Modifiable lifestyle factors have a larger contribution to colorectal neoplasms than family history.BMC cancer · 2022Article
- Improved risk scoring systems for colorectal cancer screening in Shanghai, China.Cancer medicine · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn optimal risk-scoring system enables more targeted offers for colonoscopy in colorectal cancer (CRC) screening. This analysis aims to develop and validate scoring systems using parametric and non-parametric methods for average-risk populations.
methodsScreening data of 807,695 subjects and 2806 detected cases in the first-round CRC screening program in Shanghai were used to develop risk-predictive models and scoring systems using logistic-regression (LR) and artificial-neural-network (ANN) methods. Performance of established scoring systems was evaluated using area under the receiver operating characteristic curve (AUC), calibration, sensitivity, specificity, number of high-risk individuals and potential detection rates of CRC.
resultsAge, sex, CRC in first-degree relatives, chronic diarrhoea, mucus or bloody stool, history of any cancer and faecal-immunochemical-test (FIT) results were identified as predictors for the presence of CRC. The AUC of LR-based system was 0.642 when using risk factors only in derivation set, and increased to 0.774 by further incorporating one-sample FIT results, and to 0.808 by including two-sample FIT results, while those for ANN-based systems were 0.639, 0.763 and 0.805, respectively. Better calibrations were observed for the LR-based systems than the ANN-based ones. Compared with the currently used initial tests, parallel use of FIT with LR-based systems resulted in improved specificities, less demands for colonoscopy and higher detection rates of CRC, while parallel use of FIT with ANN-based systems had higher sensitivities; incorporating FIT in the scoring systems further increased specificities, decreased colonoscopy demands and improved detection rates of CRC.
conclusionsOur results indicate the potentials of LR-based scoring systems incorporating one- or two-sample FIT results for CRC mass screening. External validation is warranted for scaling-up implementation in the Chinese population.
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