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Derivation and Validation of a Prediction Rule for Estimating Advanced Colorectal Neoplasm Risk in Average-Risk Chinese.
- Source :
- American Journal of Epidemiology; Mar2012, Vol. 175 Issue 6, p584-593, 10p
- Publication Year :
- 2012
-
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. [ABSTRACT FROM PUBLISHER]
- Subjects :
- ADENOMA
RECTUM tumors
COLON tumors
MEDICAL screening
RISK assessment
RESEARCH
AGE distribution
CALIBRATION
CANCER
CHI-squared test
COLONOSCOPY
CONFIDENCE intervals
DIABETES
DIET
DISCRIMINANT analysis
EPIDEMIOLOGY
MEDICAL cooperation
QUESTIONNAIRES
REGRESSION analysis
RESEARCH funding
STATISTICAL sampling
SEX distribution
SMOKING
STATISTICS
LOGISTIC regression analysis
DATA analysis
PREDICTIVE validity
CROSS-sectional method
RECEIVER operating characteristic curves
RESEARCH methodology evaluation
DISEASE progression
DESCRIPTIVE statistics
DISEASE risk factors
TUMOR risk factors
CANCER risk factors
Subjects
Details
- Language :
- English
- ISSN :
- 00029262
- Volume :
- 175
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- American Journal of Epidemiology
- Publication Type :
- Academic Journal
- Accession number :
- 73764628
- Full Text :
- https://doi.org/10.1093/aje/kwr337