Purpose: Colonoscopy is an effective method of screening for colorectal cancer (CRC), and it can prevent CRC by detection and removal of precancerous lesions. The most important considerations when performing colonoscopy screening are the safety and satisfaction of the patient and the diagnostic accuracy. Accordingly, the Korean Society of Coloproctology (KSCP) herein proposes an optimal level of standard performance to be used in endoscopy units and by individual colonoscopists for screening colonoscopy. These guidelines establish specific criteria for assessment of safety and quality in screening colonoscopy. Methods: The Colonoscopy Committee of the KSCP commissioned this Position Statement. Expert gastrointestinal surgeons representing the KSCP reviewed the published evidence to identify acceptable quality indicators and indicators that lacked sufficient evidence. Results: The KSCP recommends an optimal standard list for quality control of screening colonoscopy in the following 6 categories: training and competency of the colonoscopist, procedural quality, facilities and equipment, performance indicators and auditable outcomes, disinfection of equipment, and sedation and recovery of the patient. Conclusion The KSCP recommends that endoscopy units performing CRC screening evaluate 6 key performance measures during daily practice.

PURPOSE: Predicting lymph node metastasis (LNM) risk is crucial in determining further treatment strategies following endoscopic resection of T1 colorectal cancer (CRC). This study aimed to establish a new prediction model for the risk of LNM in T1 CRC patients. MATERIALS AND METHODS: The development set included 833 patients with T1 CRC who had undergone endoscopic (n=154) or surgical (n=679) resection at the National Cancer Center. The validation set included 722 T1 CRC patients who had undergone endoscopic (n=249) or surgical (n=473) resection at Daehang Hospital. A logistic regression model was used to construct the prediction model. To assess the performance of prediction model, discrimination was evaluated using the receiver operating characteristic (ROC) curves with area under the ROC curve (AUC), and calibration was assessed using the Hosmer-Lemeshow (HL) goodness-of-fit test. RESULTS: Five independent risk factors were determined in the multivariable model, including vascular invasion, high-grade histology, submucosal invasion, budding, and background adenoma. In final prediction model, the performance of the model was good that the AUC was 0.812 (95% confidence interval [CI], 0.770 to 0.855) and the HL chi-squared test statistic was 1.266 (p=0.737). In external validation, the performance was still good that the AUC was 0.771 (95% CI, 0.708 to 0.834) and the p-value of the HL chi-squared test was 0.040. We constructed the nomogram with the final prediction model. CONCLUSION: We presented an externally validated new prediction model for LNM risk in T1 CRC patients, guiding decision making in determining whether additional surgery is required after endoscopic resection of T1 CRC.
Adenoma ; Area Under Curve ; Calibration ; Colorectal Neoplasms ; Decision Making ; Discrimination (Psychology) ; Humans ; Logistic Models ; Lymph Nodes ; Neoplasm Metastasis ; Nomograms ; Risk Factors ; ROC Curve