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Impact of Age on the Risk of Advanced Colorectal Neoplasia in a Young Population: An Analysis Using the Predicted Probability Model

Authors
Jung, Yoon SukPark, Chan HyukKim, Nam HeeLee, Mi YeonPark, Dong Il
Issue Date
Sep-2017
Publisher
SPRINGER
Keywords
Advanced colorectal neoplasia; Probability; Predictive model; Young population
Citation
DIGESTIVE DISEASES AND SCIENCES, v.62, no.9, pp.2518 - 2525
Indexed
SCIE
SCOPUS
Journal Title
DIGESTIVE DISEASES AND SCIENCES
Volume
62
Number
9
Start Page
2518
End Page
2525
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/4086
DOI
10.1007/s10620-017-4683-y
ISSN
0163-2116
Abstract
Background: The incidence of colorectal cancer is decreasing in adults aged ≥50 years and increasing in those aged <50 years.) Aims: We aimed to establish risk stratification model for advanced colorectal neoplasia (ACRN) in persons aged <50 years.) Methods: We reviewed the records of participants who had undergone a colonoscopy as part of a health examination at two large medical examination centers in Korea. By using logistic regression analysis, we developed predicted probability models for ACRN in a population aged 30–49 years. Results: Of 96,235 participants, 57,635 and 38,600 were included in the derivation and validation cohorts, respectively. The predicted probability model considered age, sex, body mass index, family history of colorectal cancer, and smoking habits, as follows: Y ACRN = −8.755 + 0.080·X age − 0.055·X male + 0.041·X BMI + 0.200·X family_history_of_CRC + 0.218·X former_smoker + 0.644·X current_smoker. The optimal cutoff value for the predicted probability of ACRN by Youden index was 1.14%. The area under the receiver-operating characteristic curve (AUROC) values of our model for ACRN were higher than those of the previously established Asia–Pacific Colorectal Screening (APCS), Korean Colorectal Screening (KCS), and Kaminski’s scoring models [AUROC (95% confidence interval): model in the current study, 0.673 (0.648–0.697); vs. APCS, 0.588 (0.564–0.611), P < 0.001; vs. KCS, 0.602 (0.576–0.627), P < 0.001; and vs. Kaminski’s model, 0.586 (0.560–0.612), P < 0.001]. Conclusion: In a young population, a predicted probability model can assess the risk of ACRN more accurately than existing models, including the APCS, KCS, and Kaminski’s scoring models.
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