Published online Oct 7, 2020. doi: 10.3748/wjg.v26.i37.5705
Peer-review started: April 17, 2020
First decision: May 15, 2020
Revised: May 20, 2020
Accepted: September 12, 2020
Article in press: September 12, 2020
Published online: October 7, 2020
Processing time: 163 Days and 18.7 Hours
Colorectal cancer is the third leading cause of cancer globally. Screening for colorectal cancer has been shown to decrease colon cancer mortality. While colonoscopy is the best modality to screen for colon cancer, it is also the most expensive. In resource-limited countries, risk stratification may be useful to optimize colorectal cancer screening.
Few prospective risk prediction models exist for advanced neoplasia (AN) in true average-risk individuals.
To create a validated risk prediction model to predict advanced neoplasia in average risk patients.
980 consecutive, average-risk, asymptomatic patients undergoing their first screening colonoscopy were prospectively enrolled. We completed a detailed assessment of risk factors, and collected results of endoscopy findings from the endoscopy and pathology reports. Group comparisons of categorical factors were done using χ2, and for quantitative variables independent t-test or Mann Whitney tests were used based on normality of data. Multivariate logistic regression analysis was performed to identify independent predictors of AN in our cohort. Discriminatory ability of the model was assessed through the area under the curve (AUC) of the receiver-operator-characteristic curve. Model calibration was examined through observed vs expected rates of advanced neoplasia as the derived probability of AN decile groups. Internal validation of the model was done by bootstrapping. The multivariate model coefficients were used to present the percent risk of AN in nomogram format as a function of age and separately for different categories of BMI. The model coefficients were then used to develop a risk calculator.
Adenoma detection and advanced neoplasia detection rates were 36.6% (F 29%: M 45%; P < 0.001) and 5.1% (F 3.8%; M 6.5%) respectively. On multivariate analysis, the predictors of AN were age [1.036 (1.00-1.07); P = 0.048], BMI [overweight 2.21 (0.98-5.00); obese 3.54 (1.48-8.50); P = 0.018], smoking [< 40 pack-years 2.01 (1.01-4.01); ≥ 40 pack-years 3.96 (1.86-8.42); P = 0.002], and daily red meat consumption [2.02 (0.92-4.42) P = 0.079]. The model had an AUC = 0.73 (CI = 0.66-0.79, P < 0.001) and R2 = 0.8509.
The prevalence of adenoma and AN in the average-risk Lebanese population is 5.1%, similar to those in the West. Age, smoking and BMI are important predictors of AN in our study cohort, and our model had good calibration and discrimination.
In this project, we developed a risk prediction tool for advanced neoplasia at first screening colonoscopy for average risk individuals. We provide an important platform for improved risk-stratification for screening programs in resource limiting settings, although external validation of our model is needed.