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Review
. 2022 Jan 29;22(1):122.
doi: 10.1186/s12885-022-09238-4.

A risk scoring system to predict the individual incidence of early-onset colorectal cancer

Jialin Gu #  1   2 , Yan Li #  2 , Jialin Yu  1   3 , Miao Hu  1   2 , Yi Ji  1   3 , Lingchang Li  1   3 , Canhong Hu  1   3 , Guoli Wei  4   5   6   7 , Jiege Huo  8   9
Affiliations
Review

A risk scoring system to predict the individual incidence of early-onset colorectal cancer

Jialin Gu et al. BMC Cancer. .

Abstract

Background: The incidence of early-onset colorectal cancer (EOCRC) is increasing at an alarming rate and further studies are needed to identify risk factors and to develop prevention strategies.

Methods: Risk factors significantly associated with EOCRC were identified using meta-analysis. An individual risk appraisal model was constructed using the Rothman-Keller model. Next, a group of random data sets was generated using the binomial distribution function method, to determine nodes of risk assessment levels and to identify low, medium, and high risk populations.

Results: A total of 32,843 EOCRC patients were identified in this study, and nine significant risk factors were identified using meta-analysis, including male sex, Caucasian ethnicity, sedentary lifestyle, inflammatory bowel disease, and high intake of red meat and processed meat. After simulating the risk assessment data of 10,000 subjects, scores of 0 to 0.0018, 0.0018 to 0.0036, and 0.0036 or more were respectively considered as low-, moderate-, and high-risk populations for the EOCRC population based on risk trends from the Rothman-Keller model.

Conclusion: This model can be used for screening of young adults to predict high risk of EOCRC and will contribute to the primary prevention strategies and the reduction of risk of developing EOCRC.

Keywords: Early-onset colorectal cancer; Meta-analysis; Risk assessment; Risk factors; Rothman–Keller model.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1
The flow chart of the study selection and identification
Fig. 2
Fig. 2
The predictive analysis of Rothman–Keller model for EOCRC
See this image and copyright information in PMC

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