临床与病理杂志2025，Vol.45Issue(4)：443-451,9.DOI:10.11817/j.issn.2095-6959.2025.240919
阿奇霉素治疗肺炎支原体肺炎发生不良反应列线图预测模型的构建与验证
Construction and validation of a nomogram predictive model for adverse drug reactions to azithromycin in the treatment of Mycoplasma pneumoniae pneumonia
摘要
Abstract
Objective:Azithromycin is widely used in the treatment of Mycoplasma pneumoniae pneumonia;However,it carries a risk of adverse drug reactions(ADRs).Identifying risk factors for ADRs and constructing predictive models can provide clinical guidance.This study aims to identify risk factors for ADRs associated with azithromycin treatment in Mycoplasma pneumoniae pneumonia and to construct and validate a nomogram predictive model. Methods:A total of 700 pediatric patients with Mycoplasma pneumoniae pneumonia treated with azithromycin between January 2023 and December 2024 at three hospitals were retrospectively analyzed.Based on the occurrence of ADRs,patients were divided into an ADR group(n=143)and a non-ADR group(n=557).Clinical data including age,sex,allergy history,body mass index(BMI),treatment duration,number of concomitant medications,and laboratory indicators were collected.Logistic regression was used to identify risk factors,and a nomogram model was constructed.Internal validation was performed using the Bootstrap method(1 000 resamplings).Model performance was assessed using receiver operating characteristic(ROC)curves,calibration plots,and decision curve analysis(DCA). Results:Statistically significant differences(all P<0.05)were observed between the ADR and non-ADR groups in terms of age distribution,allergy history,BMI,number of concomitant medications,treatment duration,and lung consolidation.Logistic regression revealed that allergy history,high BMI,prolonged treatment duration,and>3 concomitant medications were risk factors(all P<0.05),while school-age(7-13 years)was a protective factor(P<0.05).The nomogram model achieved an area under the ROC curve(AUC)of 0.863[95%confidence interval(CI)0.834 to 0.891],indicating good predictive performance.The calibration curve fit closely with the ideal curve,and DCA showed high net benefit across a threshold probability range of 9.00%-91.70%. Conclusion:The nomogram model constructed using variables such as allergy history,BMI,treatment duration,number of concomitant drugs,and age distribution can effectively predict the risk of ADRs to azithromycin in children with Mycoplasma pneumoniae pneumonia.This tool can assist clinicians in early identification of high-risk patients and guide individualized medication plans.关键词
肺炎支原体肺炎/阿奇霉素/肺炎支原体/药品不良反应/危险因素/列线图/预测效能Key words
Mycoplasma pneumoniae pneumonia/azithromycin/Mycoplasma pneumoniae/adverse drug reaction/risk factors/nomogram/predictive performance引用本文复制引用
杜博英,郭在强,刘杰,马维维..阿奇霉素治疗肺炎支原体肺炎发生不良反应列线图预测模型的构建与验证[J].临床与病理杂志,2025,45(4):443-451,9.基金项目
河北省中医药管理局科研计划项目(2022489).This work was supported by the Scientific Research Plan Project of the Traditional Chinese Medicine Administration of Hebei Province,China(2022489). （2022489）
