Establishment of a prognostic nomogram to identify optimal candidates for local treatment among patients with local recurrent nasopharyngeal carcinoma.

OBJECTIVE: Thus far, there is no final conclusion on the treatment of local recurrent nasopharyngeal carcinoma (lrNPC) patients. Herein, we developed a nomogram which combined prognostic biomarkers to predict clinical outcome and guide individual treatment. MATERIALS AND METHODS: From 2006 to 2016, 303 patients with lrNPC were retrospectively reviewed. Overall survival (OS) was the primary endpoint. The nomogram was established with the significant prognostic factors (P < 0.05) selected by multivariate analysis using Cox regression model. Harrell Concordance Index (C-index), calibration curves, and decision curve analysis (DCA) were applied to evaluate this model. RESULTS: Four independent prognostic factors (age, hypertension, relapsed T (rT) stage, and Epstein-Barr virus DNA) identified from multivariable analysis were included into the nomogram. The C-index of the nomogram was 0.687. The calibration curves for 1-, 3-, and 5-year OS rate showed satisfactory agreements between the predicted and actual values. The decision curve analysis also exhibited a preferable net benefit of this model. All patients were subdivided into three risk groups based on the nomogram. Local treatment was associated with higher OS than palliative chemotherapy alone in the low (P < 0.001) and intermediate-risk groups (P = 0.001). However, no significant difference was observed between different treatment methods in the high-risk group (P = 0.176). CONCLUSION: We established the nomogram for patients with lrNPC to predict OS and guide individual treatment, which showed satisfactory performance in accuracy, discrimination capability, and clinical utility.