| Popis: |
Background: Parathyroid carcinoma is a rare endocrine malignancy. Considering that clinicians develop appropriate treatment strategies based on patients' survival expectations. Therefore, the present study aimed to develop a survival prediction model to guide clinical decision-making. Methods: We retrospectively analyzed 362 parathyroid carcinoma patients diaagnosed in the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Correlations between outcome events and variables were analyzed using univariate and multifactorial Cox regression, and variables screened by the multifactorial Cox risk proportional model were used to construct a survival prediction model. The model was evaluated using Receiver Operating Characteristic (ROC) curves, decision curve analysis (DCA), and C-index and calibration curves. Results: Univariate and multifactorial COX analyses revealed five independent prognostic factors for parathyroid carcinoma patients, which were subsequently used to develop the nomogram prediction model. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.747 (0.686–0.808), the area under the receiver operator characteristics curve(AUC)values of the nomogram in prediction of the 3, 5, and 10-year OS were 0.718 (0617-0.819), 0.711 (0.614–0.808) and 0.706 (0.610–0.803), respectively. In the validation cohort, the C-index was 0.740 (0.645–0.835), The AUC for 3, 5, and 10-years OS were 0.736 (0.584–0888), 0.698 (0.551–0.845) and 0.767 (0.647–0.887), respectively. The C-index, time-dependent ROC curve, calibration curve, and DCA showed that the Nomogram had a clear advantage. Conclusion: The developed nomogram can be applied in clinical practice to help clinicians to assess patient prognosis. |
