Skip to main content

Advertisement

Log in

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

  • Original Article
  • Published:
Digestive Diseases and Sciences Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Yeoh K, Ho K, Chiu H, et al. The Asia-Pacific Colorectal Screening score: a validated tool that stratifies risk for colorectal advanced neoplasia in asymptomatic Asian subjects. Gut. 2011;60:1236–1241.

    Article  PubMed  Google Scholar 

  2. Kim DH, Cha JM, Shin HP, et al. Development and validation of a risk stratification-based screening model for predicting colorectal advanced neoplasia in Korea. J Clin Gastroenterol. 2015;49:41–49.

    Article  CAS  PubMed  Google Scholar 

  3. Kaminski MF, Polkowski M, Kraszewska E, et al. A score to estimate the likelihood of detecting advanced colorectal neoplasia at colonoscopy. Gut. 2014;63:1112–1119.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Schroy PC, Wong JB, O’Brien MJ, et al. A risk prediction index for advanced colorectal neoplasia at screening colonoscopy. Am J Gastroenterol. 2015;110:1062–1071.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Rex DK, Johnson DA, Anderson JC, et al. American College of Gastroenterology guidelines for colorectal cancer screening 2009 [corrected]. Am J Gastroenterol. 2009;104:739–750.

    Article  PubMed  Google Scholar 

  6. Lee BI, Hong SP, Kim SE, et al. Korean guidelines for colorectal cancer screening and polyp detection. Clin Endosc. 2012;45:25–43.

    Article  PubMed  PubMed Central  Google Scholar 

  7. O’Connell JB, Maggard MA, Liu JH, et al. Rates of colon and rectal cancers are increasing in young adults. Am Surg. 2003;69:866–872.

    PubMed  Google Scholar 

  8. Inra JA, Syngal S. Colorectal cancer in young adults. Dig Dis Sci. 2015;60:722–733. doi:10.1007/s10620-014-3464-0.

    Article  PubMed  Google Scholar 

  9. Bailey CE, Hu C, You YN, et al. Increasing disparities in the age-related incidences of colon and rectal cancers in the United States, 1975–2010. JAMA Surg. 2015;150:17–22.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Chiang J, Chen M, Changchien CR, et al. Favorable influence of age on tumor characteristics of sporadic colorectal adenocarcinoma: patients 30 years of age or younger may be a distinct patient group. Dis Colon Rectum. 2003;46:904–910.

    Article  PubMed  Google Scholar 

  11. Jung YS, Ryu S, Chang Y, et al. Risk factors for colorectal neoplasia in persons aged 30 to 39 years and 40–49 years. Gastrointest Endosc. 2015;81:e637.

    Article  Google Scholar 

  12. Chang LC, Wu MS, Tu CH, et al. Metabolic syndrome and smoking may justify earlier colorectal cancer screening in men. Gastrointest Endosc. 2014;79:961–969.

    Article  PubMed  Google Scholar 

  13. Soweid AM, Kobeissy AA, Jamali FR, et al. A randomized single-blind trial of standard diet versus fiber-free diet with polyethylene glycol electrolyte solution for colonoscopy preparation. Endoscopy. 2010;42:633–638.

    Article  CAS  PubMed  Google Scholar 

  14. Rodu B, Cole P. Smoking prevalence: a comparison of two American surveys. Public Health. 2009;123:598–601.

    Article  CAS  PubMed  Google Scholar 

  15. Lieberman DA, Rex DK, Winawer SJ, et al. Guidelines for colonoscopy surveillance after screening and polypectomy: a consensus update by the US Multi-Society Task Force on Colorectal Cancer. Gastroenterology. 2012;143:844–857.

    Article  PubMed  Google Scholar 

  16. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–845.

    Article  CAS  PubMed  Google Scholar 

  17. Anonymous. Korean Statistical Information Service, Cancer incident cases and incidence rates by site (24 items), sex, age group, http://kosis.kr/statHtml/statHtml.do?orgId=117&tblId=DT_117N_A00023&conn_path=I2&language=en. Accessed Dec 19, 2016.

  18. Freedman AN, Slattery ML, Ballard-Barbash R, et al. Colorectal cancer risk prediction tool for white men and women without known susceptibility. J Clin Oncol. 2009;27:686–693.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chan Hyuk Park.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflicts of interest.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 16 kb)

Supplementary material 2 (DOCX 22 kb)

Supplementary material 3 (DOCX 17 kb)

10620_2017_4683_MOESM4_ESM.tif

Figure S1. The distribution of PAC-50 in the derivation cohort. The widths of the deep green plots represent the probability density of the data at different values. The light green plots represent the smoothed probability density after adjustment. The white circle and the gray box represent the median and interquartile range of PAC-50. The blue circles represent PAC-50 of 21 individuals who had colorectal cancer. PAC-50, probability of advanced colorectal neoplasia in a population aged < 50 years (TIFF 533 kb)

Supplementary material 5 (XLSX 13 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jung, Y.S., Park, C.H., Kim, N.H. et al. Impact of Age on the Risk of Advanced Colorectal Neoplasia in a Young Population: An Analysis Using the Predicted Probability Model. Dig Dis Sci 62, 2518–2525 (2017). https://doi.org/10.1007/s10620-017-4683-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10620-017-4683-y

Keywords

Navigation