Derivation and validation of a prediction rule for estimating advanced colorectal neoplasm risk in average-risk Chinese

Am J Epidemiol. 2012 Mar 15;175(6):584-93. doi: 10.1093/aje/kwr337. Epub 2012 Feb 10.

Abstract

No prediction rule is currently available for advanced colorectal neoplasms, defined as invasive cancer, an adenoma of 10 mm or more, a villous adenoma, or an adenoma with high-grade dysplasia, in average-risk Chinese. In this study between 2006 and 2008, a total of 7,541 average-risk Chinese persons aged 40 years or older who had complete colonoscopy were included. The derivation and validation cohorts consisted of 5,229 and 2,312 persons, respectively. A prediction rule was developed from a logistic regression model and then internally and externally validated. The prediction rule comprised 8 variables (age, sex, smoking, diabetes mellitus, green vegetables, pickled food, fried food, and white meat), with scores ranging from 0 to 14. Among the participants with low-risk (≤3) or high-risk (>3) scores in the validation cohort, the risks of advanced neoplasms were 2.6% and 10.0% (P < 0.001), respectively. If colonoscopy was used only for persons with high risk, 80.3% of persons with advanced neoplasms would be detected while the number of colonoscopies would be reduced by 49.2%. The prediction rule had good discrimination (area under the receiver operating characteristic curve = 0.74, 95% confidence interval: 0.70, 0.78) and calibration (P = 0.77) and, thus, provides accurate risk stratification for advanced neoplasms in average-risk Chinese.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adenoma* / diagnosis
  • Adenoma* / etiology
  • Adult
  • Age Factors
  • Aged
  • China
  • Colonoscopy*
  • Colorectal Neoplasms* / diagnosis
  • Colorectal Neoplasms* / etiology
  • Cross-Sectional Studies
  • Decision Support Techniques*
  • Early Detection of Cancer*
  • Female
  • Humans
  • Logistic Models
  • Male
  • Mass Screening
  • Middle Aged
  • ROC Curve
  • Risk Assessment
  • Sex Factors
  • Surveys and Questionnaires