Prediction of postoperative dysphagia in patients with oral cancer: A prospective cohort study.

ABSTRACT

OBJECTIVES: This study aims to identify autonomous risk factors for postoperative dysphagia in oral cancer patients and construct a nomogram prediction model to improve risk assessment accuracy and feasibility in clinical settings. METHODS: A prospective cohort study was conducted from March to July 2022 among oral cancer patients undergoing surgical interventions at the Department of Head and Neck Surgery. Clinical data were collected using the Postoperative Dysphagia Risk Factor Questionnaire. Swallowing function was assessed with the Mann Assessment of Swallowing Ability-Oral Cancer (MASA-OC). Lasso regression identified potential predictor variables, followed by univariate and multivariate logistic regression analyses. A predictive model was developed using R Studio 4.1.2 and rigorously evaluated with ROC curves, Hosmer-Lemeshow tests, and calibration curves. Internal validation utilized Bootstrap methodology with 1000 repetitive samples. RESULTS: The cohort included 257 oral cancer patients, with 73.9 % experiencing postoperative dysphagia. Independent predictors included functional status, depressive symptoms, pT stage, surgical techniques, glossoplasty, maxillectomy, and post-surgery nasopharyngeal tube retention. The predictive model achieved an AUC of 0.933, sensitivity of 90.9 %, and specificity of 81.7 %. Hosmer-Lemeshow test (P = 0.715) and C-index (0.934) indicated satisfactory model fit. Internal validation yielded an AUC of 0.912, sensitivity of 93.3 %, and specificity of 63.8 %. Calibration curves demonstrated alignment between predicted and observed outcomes. CONCLUSION: A nomogram integrating recognized risk factors shows promise in predicting postoperative dysphagia in oral cancer patients, enhancing precision and aiding healthcare professionals in risk evaluation and patient care strategies.