Prediction model of recurrence after parathyroidectomy in secondary hyperparathyroidism

Abstract

Objective:To quantitatively evaluate the risk of recurrence in patients with secondary hyperparathyroidism after parathyroidectomy. Methods:The clinical data of 168 patients who underwent parathyroidectomy（PTX） from June 2017 to May 2019 were collected. The prediction model was constructed by using Akaike information criterion（AIC） to screen factors. A total of 158 patients treated with PTX from June 2019 to September 2021 were included in the validation set to conduct external validation of the model in three aspects of differentiation, consistency and clinical utility. Results:The prediction model we constructed includes different dialysis methods, ectopic parathyroid gland, the iPTH level at one day and one month after surgery, the number of excisional parathyroid and postoperative blood phosphorus. The C index of external validation of this model is 0.992 and the P value of the Calibration curve is 0.886[KG0.5mm]1. The decision curve analysis also shows that the evaluation effect of this model is perfect. Conclusion:The prediction model constructed in this study is useful for individualized prediction of recurrence after PTX in patients with secondary hyperparathyroidism.