Nomogram to predict the early postoperative hypoparathyroidism after total thyroidectomy in the thyroid cancer patients of eastern China.

Background: Hypoparathyroidism is a frequent and impactful complication following total thyroidectomy for thyroid cancer. Accurate preoperative identification of high-risk patients remains challenging. This study aimed to develop and validate a nomogram to predict early postoperative hypoparathyroidism in thyroid cancer patients from Eastern China. Methods: A retrospective analysis was conducted on 1,025 thyroid cancer patients who underwent thyroidectomy at a single institution between 2018 and 2021. Patients were randomly divided into training (n=717) and validation (n=308) cohorts. Early hypoparathyroidism was defined as parathyroid hormone (PTH) <15 pg/mL within 24-48 hours postoperatively. Univariate and multivariate logistic regression analyses identified independent predictors. These were used to construct a nomogram, which was evaluated for discrimination using the area under the curve (AUC) and for calibration using calibration plots. Clinical utility was assessed via decision curve analysis (DCA). Results: Candidate variables were first screened via univariate analysis, yielding nine factors significantly associated with postoperative hypoparathyroidism. These nine factors were subsequently entered into a multivariate logistic regression model, which identified seven of them as independent predictors. These included the following significant risk factors: multifocality, higher T stage (T2, T3-4), bilateral central lymph node dissection, and dissection of ≥20 lymph nodes. Protective factors comprised the absence of incidental parathyroidectomy, higher preoperative PTH, and higher preoperative serum calcium. To optimize predictive performance and clinical utility, all nine factors from the univariate screening were incorporated into the final nomogram. The nomogram demonstrated good predictive performance, with AUC values of 0.783 [95% confidence interval (CI): 0.748-0.818] in the training set and 0.823 (95% CI: 0.775-0.871) in the validation set. Calibration curves indicated satisfactory agreement between predicted and observed probabilities, and DCA confirmed the clinical utility of the nomogram, showing a higher net benefit across a broad range of threshold probabilities. Conclusions: We developed and validated an effective nomogram for predicting early postoperative hypoparathyroidism after total thyroidectomy. This tool, based on readily available preoperative and intraoperative variables, can facilitate individualized risk stratification, potentially guiding proactive postoperative management to mitigate the burden of this complication. Prospective validation is recommended to confirm its generalizability.