Published online Jul 15, 2023. doi: 10.4251/wjgo.v15.i7.1271
Peer-review started: April 1, 2023
First decision: April 19, 2023
Revised: April 27, 2023
Accepted: May 22, 2023
Article in press: May 22, 2023
Published online: July 15, 2023
Processing time: 101 Days and 22.1 Hours
No single endoscopic feature can reliably predict the pathological nature of colorectal tumors (CRTs).
To establish and validate a simple online calculator to predict the pathological nature of CRTs based on white-light endoscopy.
This was a single-center study. During the identification stage, 530 consecutive patients with CRTs were enrolled from January 2015 to December 2021 as the derivation group. Logistic regression analysis was performed. A novel online calculator to predict the pathological nature of CRTs based on white-light images was established and verified internally. During the validation stage, two series of 110 images obtained using white-light endoscopy were distributed to 10 endoscopists [five highly experienced endoscopists and five less experienced endoscopists (LEEs)] for external validation before and after systematic training.
A total of 750 patients were included, with an average age of 63.6 ± 10.4 years. Early colorectal cancer (ECRC) was detected in 351 (46.8%) patients. Tumor size, left semicolon site, rectal site, acanthosis, depression and an uneven surface were independent risk factors for ECRC. The C-index of the ECRC calculator prediction model was 0.906 (P = 0.225, Hosmer–Lemeshow test). For the LEEs, significant improvement was made in the sensitivity, specificity and accuracy (57.6% vs 75.5%; 72.3% vs 82.4%; 64.2% vs 80.2%; P < 0.05), respectively, after training with the ECRC online calculator prediction model.
A novel online calculator including tumor size, location, acanthosis, depression, and uneven surface can accurately predict the pathological nature of ECRC.
Core Tip: White light endoscopy remains the most basic and indispensable tool in diagnosing colorectal tumors (CRTs). No single endoscopic feature can reliably predict the pathological nature of CRTs. Here, we investigated the endoscopic findings of CRTs, including lobulation, erosion, expansion, depression, acanthosis, lifting sign, stiffness, nodules larger than 10 mm, and so on. A logistic regression analysis was performed, and a novel online calculator for predicting the pathological nature of CRTs based on white-light imaging was established and verified.