Frontiers in Neuroscience (Feb 2022)
Prognostic Analysis for Patients With Parathyroid Carcinoma: A Population-Based Study
Abstract
BackgroundParathyroid carcinoma (PC) is a rare but often lethal malignancy for which staging system, prognostic indicators, and treatment guidelines are still not established. We aimed to explore the prognostic parameters and construct a nomogram for cancer-specific survival (CSS) of PC.MethodsA retrospective analysis of 604 PC patients in the SEER database from 2001 through 2018 was performed. All the cases were randomly assigned to the training cohort (n = 424) or the validation cohort (n = 180) at a ratio of 7:3. The Kaplan–Meier method and Cox regression model were applied to estimate the CSS and risk factors, and a nomogram was constructed. The predictive accuracy and discriminative ability of the nomogram in CSS were assessed by concordance index (C-index), the area under the curve (AUC) of receiver operating characteristics (ROC), and the calibration curve.ResultsAge at diagnosis > 70 years [hazard ratio (HR): 3.55, 95% CI: 1.07–11.78, p = 0.039] and tumor size > 35 mm (HR 4.22, 95% CI: 1.67–10.68, p = 0.002) were associated with worse CSS. Compared with distant metastasis, localized (HR 0.17, 95% CI: 0.06–0.47, p = 0.001) and regional lesions (HR 0.22, 95% CI: 0.07–0.66, p = 0.007) showed an improved CSS rate. Parathyroidectomy was the recommended treatment (p = 0.02). The C-index of the nomogram was 0.826, and the AUC for 5-, 10-, and 15-year CSS was 83.7%, 79.7%, and 80.7%, respectively. The calibration curve presented good agreement between prediction by nomogram and actual observation.ConclusionAge at diagnosis > 70 years, tumor size > 35 mm, and distant metastasis were independent risk factors for PC-specific mortality. Parathyroidectomy was currently the most recommended treatment for PC. This nomogram provided individualized assessment and reliable prognostic prediction for patients with PC.
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