A clinical model for predicting lymph node metastasis in submucosal invasive (T1) colorectal cancer.

ABSTRACT

BACKGROUND: No single histopathological feature of submucosal invasive colorectal cancer (T1-CRC) can reliably predict the risk for lymph node metastasis (LNM). AIM: The purpose of the study was to develop a prediction model of LNM in T1-CRC. METHODS: Ninety-seven surgically resected T1-CRC at our institution were retrospectively evaluated. Morphology, localization, grading, mode of growth, presence of background adenoma, lymphoid infiltration, angiolymphatic invasion, budding, and depth of invasion were assessed. Mortality and morbidity related to surgery were also evaluated. Benefit-risk balance was assessed according to the presence of severe complications and to the presence of LNM. RESULTS: Fourteen cases had LNM (14%). Eight patients (8%) presented severe surgical complications and there were two deaths (2 %). Infiltrative growth pattern (OR 31.91, 95% CI 2.37-428.36; p = 0.009) and the absence of lymphoid infiltrate (OR 28.75; 95% CI 2.13-388.37; p = 0.011) were the only variables independently associated with LNM in the multivariate analysis. Both variables were included in the prediction model together with sessile morphology (OR 4.88; 95% CI 0.81-29.3; p = 0.083) and poorly differentiated carcinoma (OR 11.77; 95% CI 0.77-179.83; p = 0.076). A 0-100 score was developed (infiltrative growth pattern no = 0, yes = 33; lymphoid infiltrate no = 29, yes = 0; sessile morphology no = 0, yes = 15; poorly differentiated no = 0, yes = 23). Cutoff point to indicate additional surgery was set in 35 points (i.e., 10% risk LNM). Discrimination of the prediction model was excellent (AUC 0.90; 95% CI 0.81-0.99). CONCLUSION: Combined evaluation of infiltrative growth pattern, lymphoid infiltration, poorly differentiated carcinoma, and sessile appearance showed good performance for discriminating T1-CRC patients with LNM. The benefit-risk balance was in favor of surgery when at least two of these criteria were present.