Abstract
Colorectal cancer is the leading cause of cancer-related deaths worldwide, and early detection has proven to be an effective method for reducing mortality. The machine learning method can be implemented to build a noninvasive stratifying tool that helps identify patients with potential colorectal precancerous lesions (polyps). This study aimed to develop a noninvasive risk-stratified tool for colorectal polyps in asymptomatic, healthy participants. A total of 20,129 consecutive asymptomatic patients who underwent a health checkup between January 2005 and August 2007 were recruited. Positive relationships between noninvasive risk factors, such as age, Helicobacter pylori infection, hypertension, gallbladder polyps/stone, and BMI and colorectal polyps were observed (p < 0.0001), regardless of sex, whereas significant findings were noted in men with tooth disease (p = 0.0053). A risk stratification tool was developed, for colorectal polyps, that considers annual checkup results from noninvasive examinations. For the noninvasive stratified tool, the area under the receiver operating characteristic curve (AUC) of obese females (males) aged <50 years was 91% (83%). In elderly patients (>50 years old), the AUCs of the stratifying tools were >85%. Our results indicate that the risk stratification tool can be built by using random forest and serve as an efficient noninvasive tool to identify patients requiring colonoscopy.
Highlights
Colorectal cancer (CRC) is the most common cancer worldwide and a significant public health problem in developed countries [1,2]
This study aimed to develop a simple, noninvasive, risk factor, and noninvasive risk stratification tool for these asymptomatic populations to determine colorectal precancerous lesions
Logistic regression analysis was performed after adjusting for age, gender, BMI, GB polyp/stone, tooth disease, hypertension, and Helicobacter pylori infection to determine independent predictors of colorectal polyps
Summary
Colorectal cancer (CRC) is the most common cancer worldwide and a significant public health problem in developed countries [1,2]. Removal of all precancerous lesions during endoscopy has been the most effective method for preventing cancer development [6,7,8]. Colonoscopy is the most effective method for the search and removal of colorectal polyps. Previous studies have reported several adverse events of colonoscopy, including perforation (0.005–0.085%) and bleeding (0.0001–0.687%) [9]. These adverse events create health hazards for patients and financial burdens for healthcare centers
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