Establishment of a nomogram model for predicting distant metastasis in oncocytic thyroid carcinoma: A retrospective cohort study.

Oncocytic thyroid carcinoma (OCA) is a rare subtype of thyroid cancer, the patients with distant metastases frequently present a relatively poor survival prognosis. This study aims to establish a nomogram model for predicting the occurrence of distant metastasis in OCA. Data from 770 patients (from 2004-2021) were extracted from the Surveillance, Epidemiology, and End Results database for a retrospective study. The cancer-specific survival of OCA patients with different characteristics was assessed using Kaplan-Meier subgroup analysis curves. Using univariate and multivariate logistic regression analysis methods to identify independent risk factors for establishing a nomogram to predict the risk of distant metastasis. The predictive efficiency of the model was evaluated using the area under the curve, concordance index, and calibration curves. The clinical value of the predictive model was determined through decision curves analysis. Kaplan-Meier analysis found significant differences in cancer-specific survival among groups with different ages, tumor-node-metastasis stages, tumor sizes, and lymph node ratio. Through univariate and multivariate logistic regression, it was identified that age ≥ 55 years, higher T stage (T4), and higher N stage (N1a/N1b) are significant in diagnosing distant metastasis in OCA patients, leading to the establishment of a nomogram model. The model area under the curve and concordance index were 0.903, and calibration curves and the model decision curves analysis curve evaluated its feasibility and clinical utility. Extracting age, T stage, and N stage to establish a predictive model for distant metastasis in OCA patients. The nomogram is of great significance for clinicians to timely identify high-risk patients for distant metastasis and make further clinical decisions.