AUTHOR=Tao Mei , Luo Shuyan , Wang Xiaoming , Jia Meng , Lu Xiubo 

TITLE=A Nomogram Predicting the Overall Survival and Cancer-Specific Survival in Patients with Parathyroid Cancer: A Retrospective Study

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.850457

DOI=10.3389/fendo.2022.850457

ISSN=1664-2392

ABSTRACT=Purpose: This study aimed to explore a visual model for predicting the prognosis of patients with parathyroid carcinoma (PC) and analyze related biochemistries  in different groups of stage.
Methods: The training dataset of 342 patients with PC was obtained from the SEER database, and the validation dataset included 59 patients from The First Affiliated Hospital of Zhengzhou University. Uni- and multivariate Cox regression analyses were performed to evaluate significant independent prognostic factors. Based on those factors, nomograms and web-based probability calculators were constructed to evaluate the overall survival (OS) and the cancer-specific survival (CSS) at 3, 5 and 8 years. C-index, receiver operating curve, calibration curve, and decision curve analysis were used to evaluate the nomogram in training set and validation set. Moreover, biochemistries from the validation set were retrospectively analyzed in different groups of stage by Kruskal-Wallis test
Results: Age, marital status, tumor size, stage, lymph node status, and radiation were identified as prognostic factors of OS. In contrast, only tumor size and stage were predictive for CSS. The nomogram was developed based on these independent factors. The C-index, ROC, calibration curve, and DCA curve of the nomogram in both training and validation sets showed that the nomogram had good predictive value, stability, and clinical benefit in predicting 3-, 5-, and 8-year OS and CSS in PC patients. Among the 59 PC patients from our hospital, lower albumin levels and higher postoperative parathyroid hormone levels were found in patients with distant diseases (Distant vs. Regional ALB levels: p=0.037; Distant vs. Local ALB levels: p=0.046; Distant vs. Regional postoperative PTH levels: p=0.002; Distant vs. Local postoperative PTH: p=0.002;).