Three pathologic criteria for reproducible diagnosis of colonic sessile serrated lesion versus hyperplastic polyp

Colonic SSLs are thought to predispose to w30% of colonic adenocarcinomas. This increased risk, compared to benign HPs, makes their distinction vitally important. However, no gold standard exists to differentiate them, and wide observer variability is reported. To better distinguish these polyps, we investigated 94 serrated polyps (53 SSLs and 41 HPs) using an easy-to-apply pathologic scoring system that combines, for the first time, three established distinguishing features: polyp morphology, location, and size. As an additional novel approach, polyp size was assessed by serrated biopsy number compared to endoscopic size. RNA expression profiling served as an additional biomarker. The considerable morphologic overlap across serrated polyps was quantitated for the first time. Interobserver variability was assessed by 8 expert gastrointestinal pathologists. By ROC analysis, polyp size by biopsy number performed best, followed by polyp location and morphology (areas under the curves [AUCs] = 85.9%, 81.2%, and 65.9%, respectively). Optimal discrimination combined all 3 features (AUC = 92.9%). For polyp size, the biopsy number proved superior to endoscopic size (AUC = 85.9% versus 55.2%, P = .001). Interobserver variability analysis yielded the highest reported Fleiss and Kappa statistics (0.879) and percent agreement (96.8%), showing great promise toward improved diagnosis. The proposed 3-criteria pathologic system, combining size by biopsy number, location, and morphology, yields an improved, easy-to-use, and highly reproducible diagnostic approach for differentiating SSLs and HPs. (c) 2023 Elsevier Inc. All rights reserved.

Automated summary

Colonic SSLs are associated with 30% of colonic adenocarcinomas. Differentiating them from benign HPs is crucial but challenging. This study developed a pathologic scoring system combining morphology, location, and size to better distinguish these polyps. The system showed promising results in improving diagnosis with high reproducibility.