Risk factors analysis and prediction model construction of submucosal deep infiltration of early colorectal tumor / 中华肿瘤杂志

Objective: To investigate the risk factors for the development of deep infiltration in early colorectal tumors (ECT) and to construct a prediction model to predict the development of deep infiltration in patients with ECT. Methods: The clinicopathological data of ECT patients who underwent endoscopic treatment or surgical treatment at the Cancer Hospital, Chinese Academy of Medical Sciences from August 2010 to December 2020 were retrospectively analyzed. The independent risk factors were analyzed by multifactorial regression analysis, and the prediction models were constructed and validated by nomogram. Results: Among the 717 ECT patients, 590 patients were divided in the within superficial infiltration 1 (SM1) group (infiltration depth within SM1) and 127 patients in the exceeding SM1 group (infiltration depth more than SM1). There were no statistically significant differences in gender, age, and lesion location between the two groups (P>0.05). The statistically significant differences were observed in tumor morphological staging, preoperative endoscopic assessment performance, vascular tumor emboli and nerve infiltration, and degree of tumor differentiation (P<0.05). Multivariate regression analysis showed that only erosion or rupture (OR=4.028, 95% CI: 1.468, 11.050, P=0.007), localized depression (OR=3.105, 95% CI: 1.584, 6.088, P=0.001), infiltrative JNET staging (OR=5.622, 95% CI: 3.029, 10.434, P<0.001), and infiltrative Pit pattern (OR=2.722, 95% CI: 1.347, 5.702, P=0.006) were independent risk factors for the development of deep submucosal infiltration in ECT. Nomogram was constructed with the included independent risk factors, and the nomogram was well distinguished and calibrated in predicting the occurrence of deep submucosal infiltration in ECT, with a C-index and area under the curve of 0.920 (95% CI: 0.811, 0.929). Conclusion: The nomogram prediction model constructed based on only erosion or rupture, local depression, infiltrative JNET typing, and infiltrative Pit pattern has a good predictive efficacy in the occurrence of deep submucosal infiltration in ECT.

Clinical value of JNET classification for non-real-time diagnosis of colorectal lesions / 中华消化内镜杂志

Objective To study the diagnostic value of Japan narrow band imaging expert team ( JNET) classification for differentiating pathological type of colorectal lesions. Methods A total of 418 colorectal lesions were retrospectively diagnosed by magnifying endoscopy with narrow band imaging ( ME-NBI) using JNET classification by two inexperienced doctors after a short time of training in JNET classification. Then lesions were diagnosed with Sano classification by the two doctors. Diagnostic results were compared with histologic findings as a golden standard. Results The sensitivity, specificity, and accuracy of JNET classification and Sano classification for neoplastic lesion differentiation were 98. 2％ VS 98. 5％, 77. 8％ VS 66. 7％, and 96. 9％ VS 96. 4％, respectively ( all P>0. 05 ) . These indicators for diagnosing cancerous lesions, including high grade intraepithelial neoplasia, intramucosal carcinoma and submucosal carcinoma, were 66. 7％ VS 80. 2％ ( P=0. 023) , 87. 6％ VS 79. 5％ ( P=0. 006) , and 82. 1％ VS 79. 7％( P=0. 379 ) , respectively, and those for predicting submucosal deep invasive cancers were 34. 8％ VS 39. 1％, 100. 0％ VS 99. 0％, and 96. 4％ VS 96. 3％, respectively ( all P>0. 05) . The diagnostic accuracy of JNET classification for differentiating neoplastic lesions were 95. 2％ in those with diameter <10 mm, 97. 0％ in 10～<20 mm, and 97. 8％ in ≥20 mm (P=0. 483), this finding were 95. 2％, 85. 1％ and 72. 1％ for cancer, respectively ( P<0. 0001 ) , and 100％, 96. 3％, and 94. 4％ for submucosal deep invasive cancer, respectively (P=0. 026). Shape and location of colorectal lesions showed no significant effect on the diagnostic efficacy of JNET classification. Conclusion JNET classification is valuable for doctors without experience of ME-NBI in diagnosing colorectal lesions and the efficiency is slightly superior to Sano classification. However, the accuracy of diagnosis for cancer with diameter ≥20 mm need to be improved.

Diagnostic value of JNET classification under narrow-band imaging for colorectal laterally spreading tumors / 中华消化内镜杂志

Objective@#To evaluate the diagnostic efficacy of Japan Narrow Band Imaging Expert Team(JNET) classification under narrow-band imaging (NBI) for colorectal laterally spreading tumors.@*Methods@#Data of 170 laterally spreading tumors (LST) detected by NBI and pigment dyeing were reviewed in the retrospective study. JNET classification under NBI was used for rediagnosis based on surface pattern and vessel pattern. Pit pattern(PP) was observed under pigment dyeing using PP classification. The results were compared with histologic results after endoscopic resection or surgery.@*Results@#The diagnostic sensitivity, specificity, positive predictive value, negative predictive value and accuracy of JNET classification and PP classification were 92.2% VS 70.3%, 82.3% VS 85.0%, 74.7% VS 72.6%, 94.9% VS 83.5%, 85.9% VS 79.7%, respectively (P=0.159). The consistency rates of JNET classification and PP classification in predicting shallow invasion depth of LST were 6.1% and 8.3% respectively and the consistency rates in predicting deep invasion were 30.8% and 4.8%, respectively.@*Conclusion@#JNET classification under NBI is effective in predicting malignant laterally spreading tumors, however, its efficacy in predicting tumor invasion depth is unsatisfied. PP classification can be used to improve the diagnostic accuracy for those with diagnostic difficulty.

Diagnostic value of JNET classification under narrow-band imaging for colorectal laterally spreading tumors / 中华消化内镜杂志

Objective To evaluate the diagnostic efficacy of Japan Narrow Band Imaging Expert Team(JNET)classification under narrow-band imaging (NBI)for colorectal laterally spreading tumors. Methods Data of 170 laterally spreading tumors (LST)detected by NBI and pigment dyeing were reviewed in the retrospective study. JNET classification under NBI was used for rediagnosis based on surface pattern and vessel pattern. Pit pattern(PP)was observed under pigment dyeing using PP classification. The results were compared with histologic results after endoscopic resection or surgery. Results The diagnostic sensitivity,specificity, positive predictive value, negative predictive value and accuracy of JNET classification and PP classification were 92. 2％ VS 70. 3％,82. 3％ VS 85. 0％,74. 7％ VS 72. 6％,94. 9％VS 83. 5％,85. 9％ VS 79. 7％,respectively (P= 0. 159). The consistency rates of JNET classification and PP classification in predicting shallow invasion depth of LST were 6. 1％ and 8. 3％ respectively and the consistency rates in predicting deep invasion were 30. 8％ and 4. 8％,respectively. Conclusion JNET classification under NBI is effective in predicting malignant laterally spreading tumors,however,its efficacy in predicting tumor invasion depth is unsatisfied. PP classification can be used to improve the diagnostic accuracy for those with diagnostic difficulty.

Diagnostic value of JNET classification for colorectal neoplasms / 中华消化内镜杂志

Objective To evaluate the clinical value of JNET classification using magnifying endoscopy with narrow-band imaging(ME-NBI)on diagnosis of colorectal neoplastic lesions. Methods A total of 110 colorectal neoplastic lesions detected by conventional colonoscopy were assessed by ME-NBI,and the histology was predicted according to characteristics of vessel pattern and surface pattern with JNET classification and Kudo classification,respectively. The results were compared with actual histologic findings of these lesions. Results The diagnostic sensitivity, specificity, positive predictive value, negative predictive value,and accuracy of overall JNET classification with ME-NBI for colorectal neoplastic lesions was 96.2%(75/78),93.8%(30/32),97.4%(75/77),90.9%(30/33), and 95.5%(105/110), respectively. The corresponding indicators of overall Kudo classification with ME-NBI was 92.3%(72/78), 81.3%(26/32),92.3%(72/78),81.3%(26/32),and 89.1%(98/110),respectively,with no significant difference compared to JNET classification(P=0.077). Diagnostic accuracy of JNET classification was 92.3%(36/39)in the polyps with diameter of 1 to 5 mm,93.8%(15/16)in the polyps with diameter of 6 to 10 mm,98.2%(54/55)in the polyps with diameter more than 10 mm, and those diagnostic accuracies had no significant difference(P=0.345). Conclusion JNET classification with ME-NBI is effective in distinguishing neoplastic from non-neoplastic colorectal lesions.