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.
目的： 探讨早期结直肠肿瘤(ECT)发生深浸润的危险因素及构建预测ECT患者发生深浸润的预测模型。 方法： 回顾性分析2010年8月至2020年12月于中国医学科学院肿瘤医院接受内镜下治疗或外科治疗的ECT患者的临床病理资料，影响因素分析采用logistic多因素回归分析，将独立危险因素通过列线图的方式构建预测模型并进行验证。 结果： 717例ECT患者中，黏膜下浅浸润(SM)1以内组590例(浸润深度在SM1以内)，超SM1组127例(浸润深度超过SM1)。SM1以内组和超SM1组患者的性别、年龄、病变位置差异均无统计学意义(均P>0.05)，肿瘤形态分型、术前内镜评估表现、脉管瘤栓和神经浸润、肿瘤分化程度差异有统计学意义(均P<0.05)。多因素回归分析显示，糜烂或破溃(OR＝4.028，95% CI：1.468~11.050，P＝0.007)、局部凹陷(OR＝3.105，95% CI：1.584~6.088，P＝0.001)、浸润性JNET分型(OR＝5.622，95% CI：3.029~10.434，P<0.001)、浸润性Pit pattern(OR＝2.722，95% CI：1.347~5.702，P＝0.006)是ECT发生黏膜下深浸润的独立危险因素。将纳入的独立危险因素构建列线图，列线图在预测ECT发生黏膜下深浸润方面具有良好的区分度和校准度，C－index及曲线下面积均为0.920(95% CI：0.811~0.929)。 结论： 基于糜烂或破溃、局部凹陷、浸润性JNET分型、浸润性Pit pattern构建的Nomogram预测模型在对ECT发生黏膜下深浸润方面具有较好的预测效能。.
Keywords: Colorectal neoplasms; Infiltration depth; JNET; Pit pattern; White light endoscope.