Feng Yingnan, Zhou Yinghui, Feng Xiaodong, Sa Qila, Zhang Ningyuan, Xie Wantao, Liu Bailiang, Chen Fengyang, Cheng Guangming, Zhang Wei
Department of Hepatobiliary Surgery, General Hospital of Northern Theater Command, Shenyang, China.
Postgraduate College, Dalian Medical University, Dalian, China.
Front Endocrinol (Lausanne). 2025 May 29;16:1584602. doi: 10.3389/fendo.2025.1584602. eCollection 2025.
We aimed to construct a predictive scoring model for the factors influencing serum phosphorus reduction following total parathyroidectomy (tPTX) in secondary hyperparathyroidism (SHPT) and provide a reference for identifying patients who can successfully correct hyperphosphatemia before surgery.
The clinical data of 529 patients with SHPT who underwent tPTX were retrospectively analyzed according to the inclusion and exclusion criteria. Univariate and multivariate analyses were conducted to determine the independent factors and establish a predictive scoring model. The receiver operating characteristic curve (ROC) was applied to verify the model in the training and validation groups, respectively.
In the whole group, 315 patients had a significant decrease in serum phosphorus after tPTX. Univariate and multivariate analysis showed that preoperative alkaline phosphatase (AKP), intact parathyroid hormone (iPTH) and free triiodothyronine (FT3) were independent influencing factors to promote the decrease of serum phosphorus after tPTX; Serum phosphorus and bone pain were inhibitory factors (all P<0.05). According to the cut-off value, AKP>193.33 U/L, iPTH>1808 pg/mL, FT3>2.825 pg/mL, serum phosphorus>2.285 mmol/L and bone pain were used to establish the predictive scoring model for serum phosphorus decline. The results showed that the success rate of serum phosphorus reduction was 67.55% at 1014 points and 95.35% at 1524 points. The area under ROC curves (AUC) for the training and validation group were 0.818 (95% CI=0.7750.861) and 0.840 (95% CI=0.7800.901, both P<0.05).
The established prediction score model for serum phosphorus decrease has a good prediction efficiency which is helpful for the early identification. The model provides important clinical guidance for the postoperative management and treatment of SHPT.
构建继发性甲状旁腺功能亢进症（SHPT）患者行甲状旁腺全切术（tPTX）后影响血清磷降低因素的预测评分模型，为术前识别能成功纠正高磷血症的患者提供参考。
根据纳入和排除标准，回顾性分析529例行tPTX的SHPT患者的临床资料。进行单因素和多因素分析以确定独立因素并建立预测评分模型。分别应用受试者工作特征曲线（ROC）在训练组和验证组中验证该模型。
全组中，315例患者tPTX后血清磷显著降低。单因素和多因素分析显示，术前碱性磷酸酶（AKP）、全段甲状旁腺激素（iPTH）和游离三碘甲状腺原氨酸（FT3）是促进tPTX后血清磷降低的独立影响因素；血清磷和骨痛是抑制因素（均P<0.05）。根据截断值，AKP>193.33 U/L、iPTH>1808 pg/mL、FT3>2.825 pg/mL、血清磷>2.285 mmol/L和骨痛用于建立血清磷下降的预测评分模型。结果显示，1014分血清磷降低成功率为67.55%，1524分成功率为95.35%。训练组和验证组的ROC曲线下面积（AUC）分别为0.818（95%CI=0.7750.861）和0.840（95%CI=0.7800.901，均P<0.05）。
建立的血清磷降低预测评分模型具有良好的预测效能，有助于早期识别。该模型为SHPT的术后管理和治疗提供了重要的临床指导。
