Predicting the acute-phase response fever risk in bisphosphonate-naive osteoporotic patients receiving their first dose of zoledronate,Osteoporosis International

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Predicting the acute-phase response fever risk in bisphosphonate-naive osteoporotic patients receiving their first dose of zoledronate
Osteoporosis International ( IF 4.2 ) Pub Date : 2022-08-03 , DOI: 10.1007/s00198-022-06493-w
Ke Lu ₁ , Qin Shi ₂ , Ya-Qin Gong ₃ , Jia-Wei Shao ₄ , Chong Li ₁

Affiliation

Introduction

To devise a precise and efficient tool for predicting the individualized risk of acute-phase response (APR) in bisphosphonate (BP)-naive osteoporotic (OP) patients, receiving their first intravenous dose of zoledronate (ZOL).

Methods

The baseline clinical and laboratory data of 475 consecutive BP-naive OP patients, who received their first intravenous dose of ZOL between March 2016 and March 2021 in the Affiliated Kunshan Hospital of Jiangsu University, were chosen for analysis. Univariate and multivariable logistic regression models were generated to establish candidate predictors of APR fever risk, using three distinct fever thresholds, namely, 37.3 °C (model A), 38.0 °C (model B), and 38.5 °C (model C). Next, using predictor regression coefficients, three fever-threshold nomograms were developed. Discrimination, calibration, and clinical usefulness of each predicting models were then assessed using the area under the curve (AUC), calibration curve (CC), and decision curve analysis (DCA). The internal and external model validations were then performed.

Results

The stable predictors were age, serum 25-hydroxy vitamin D, serum total calcium, and peripheral blood erythrocytes count. These were negatively associated with the APR fever risk. The AUCs of models A, B, and C were 0.828 (95% confidence intervals [CI], 0.782 to 0.874), 0.825 (95% CI, 0.767 to 0.883), and 0.879 (95% CI, 0.824 to 0.934), respectively. Good agreement was observed between the predictions and observations in the CCs of all three nomograms.

Conclusions

This study developed and validated nomogram prediction models that can predict APR fever risk in BP-naive OP patients receiving their first infusion of ZOL.

中文翻译：

预测接受首剂唑来膦酸盐的未使用双膦酸盐的骨质疏松症患者的急性期反应发热风险

介绍

设计一种精确有效的工具，用于预测接受首次静脉注射唑来膦酸盐 (ZOL) 的双膦酸盐 (BP) 初治骨质疏松症 (OP) 患者的急性期反应 (APR) 个体化风险。

方法

选择江苏大学附属昆山医院 2016 年 3 月至 2021 年 3 月期间接受首次静脉注射 ZOL 的 475 例连续 BP 初治 OP 患者的基线临床和实验室数据进行分析。使用三个不同的发热阈值，即 37.3 °C（模型 A）、38.0 °C（模型 B）和 38.5 °C（模型 C），生成单变量和多变量逻辑回归模型以建立 APR 发热风险的候选预测因子。接下来，使用预测回归系数，开发了三个发烧阈值列线图。然后使用曲线下面积 (AUC)、校准曲线 (CC) 和决策曲线分析 (DCA) 评估每个预测模型的区分、校准和临床有用性。然后进行内部和外部模型验证。

结果

稳定的预测因子是年龄、血清 25-羟基维生素 D、血清总钙和外周血红细胞计数。这些与 APR 发烧风险呈负相关。模型 A、B 和 C 的 AUC 分别为 0.828（95% CI，0.782 至 0.874）、0.825（95% CI，0.767 至 0.883）和 0.879（95% CI，0.824 至 0.934） . 在所有三个列线图的 CC 中的预测和观察结果之间观察到了良好的一致性。