Literature DB >> 28733868

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

Yoon Suk Jung1, Chan Hyuk Park2, Nam Hee Kim1, Mi Yeon Lee3, Dong Il Park1.   

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.

Entities:  

Keywords:  Advanced colorectal neoplasia; Predictive model; Probability; Young population

Mesh:

Year:  2017        PMID: 28733868     DOI: 10.1007/s10620-017-4683-y

Source DB:  PubMed          Journal:  Dig Dis Sci        ISSN: 0163-2116            Impact factor:   3.199


  17 in total

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