A preoperative nomogram model for the prediction of lymph node metastasis in buccal mucosa cancer

OBJECTIVES: We sought to construct a nomogram model predicting lymph node metastasis (LNM) in patients with squamous cell carcinoma of the buccal mucosa based on preoperative clinical characteristics. METHODS: Patients who underwent radical resection of a primary tumor in the buccal mucosa with neck dissection were enrolled. Clinical characteristics independently associated with LNM in multivariate analyses were adopted to build the model. Patients at low risk of LNM were defined by a predicted probability of LNM of less than 5%. RESULTS: Patients who underwent surgery in an earlier period (January 2015–November 2019) were defined as the model development cohort (n = 325), and those who underwent surgery later (November 2019–March 2021) were defined as the validation cohort (n = 140). Age, tumor differentiation, tumor thickness, and clinical N stage assessed by computed tomography/magnetic resonance imaging (cN) were independent predictors of LNM. The nomogram model based on these four predictors showed good discrimination accuracy in both the model development and validation cohorts, with areas under the receiver‐operating characteristic curve (AUC) of 0.814 and 0.828, respectively. LNM prediction by the nomogram model was superior to cN in AUC comparisons (0.815 vs. 0.753) and decision curve analysis of the whole cohort. Seventy‐one patients were defined as having a low risk of LNM, among whom the actual metastasis rate was only 1.4%. CONCLUSIONS: A robust nomogram model for preoperative LNM prediction is built.