DIAGNOSTIC PERFORMANCE OF JAPAN NBI EXPERT TEAM (JNET) CLASSIFICATION AND CONECCT CLASSIFICATION FOR LARGE COLORECTAL LATERALLY SPREADING LESIONS TREATED BY ENDOSCOPIC SUBMUCOSAL DISSECTION: A LARGE WESTERN COHORT STUDY.

Aims Endoscopic characterization aims to predict the histology of a lesion and thus the risk of cancer. This characterization step is essential, especially in the case of large superficial colorectal lesions, as the choice of resection technique directly depends on it. The JNET (Japan NBI Expert Team) classification is the classification proposed by European and Japanese guidelines to select the optimal therapeutic approach between EMR (endoscopic mucosal resection), ESD (endoscopic submucosal dissection), or surgery, but has not been evaluated in large laterally spreading lesions (LSTs) (>20 mm). We therefore evaluated the diagnostic performance of the JNET classification for predicting the risk of submucosal invasive cancer (SMIC) in LSTs >20 mm.
Methods Single-center, prospective, observational study including all patients referred for endoscopic resection of lesions >20 mm, between 2017 and 2022. All LST samples with SMIC underwent a secondary pathological examination to establish the correlation between "covert" carcinoma (SMICs categorized as JNET 2A) and "buried" carcinoma (existence of SMICs more than 0.5 mm from the surface). The primary outcome was the diagnostic accuracy of the JNET classification for histological prediction of LSTs >20 mm. The secondary objective was to assess the combined performance of the JNET classification and pejorative macroscopic (macronodule >1 cm, Paris 0-IIc area, JNET 2B area, Non-Granular LST) criteria also called the CONECCT classification. We also attempted to determine the characteristics and risk factors of LSTs with covert or buried carcinoma, and to identify potential associations between the two.
Results 972 lesions were removed by en-bloc ESD, of which 110 (11.3%) of these lesions contained SMIC. The sensitivity and specificity for predicting high-grade dysplasia (HGD) to SMIC were 46% and 75% for JNET 2B and 87% and 38% for CONECCT IIC, respectively; and for predicting superficial SMIC were 67% and 67% for JNET 2B and 94% and 27% for CONECCT IIC, respectively. CONECCT IIC was significantly more sensitive than JNET 2B for predicting HGD to superficial SMIC (46% vs. 87%; p< 0.001) and for predicting isolated superficial cancer (67% vs. 97%; p< 0.0001). And JNET 2B exhibited significantly higher specificity than CONECCT IIC for predicting HGD to superficial SMIC (75% vs. 38%; p< 0.001) and for predicting isolated superficial cancer (67% vs. 27%; p< 0.0001). No association was found between covert carcinoma and buried carcinoma.
Conclusion The JNET classification has a low diagnostic accuracy for predicting the risk of SMIC in LSTs >20 mm. The CONECCT classification has a high sensitivity for predicting SMIC. When a selective ESD and piecemeal-EMR strategy is used according to submucosal cancer risk, the CONECCT classification should be preferred to avoid undertreatment of SMIC.