基于真实世界数据研究注射用伏立康唑致急性肾损伤的危险因素建立预测模型及验证

doi:10.19803/j.1672-8629.20230530

摘要/Abstract

摘要： 目的基于真实世界数据,分析注射用伏立康唑发生急性肾损伤（AKI）的危险因素,建立预测模型并进行内部验证和外部验证,为临床安全用药提供参考。方法收集2020年1月1日至2023年6月30日在某院注射用伏立康唑治疗 ≥ 3 d,且年龄 ≥18岁患者的病历资料。其中2023年1月1日之前出院的患者作为建模组,之后的患者作为验证组。提取患者的基本信息、实验检查指标、临床诊断、联合用药等数据。根据是否发生AKI将患者分为AKI组和非AKI组。采用多因素 Logistic 回归法分析注射用伏立康唑致AKI的危险因素,并建立预测模型。通过受试者工作特征（ROC）、ROC曲线下面积（AUC）及Hosmer-Lemeshow检验（H-L检验）评估区分度和校准度,并进行内部验证和外部数据验证检验该模型的价值。结果共625例（男性371例,女性254例）患者纳入研究。其中建模组489例（男性296例,女性193例）,发生AKI 87例;验证组136例（男性75例,女性61例）,发生AKI 32例。建模组多因素 Logistic 回归分析显示血流感染、肾脏疾病、心血管疾病、使用利尿剂是发生AKI危险因素,肌酐清除率（CrCl）和血清白蛋白（Alb）是保护因素。用上述影响因素建立 Logistic 回归方程,经变换后得到预测因子Y=0.735X₁+0.707X₂+0.701X₃+0.683X₄-0.062X₅-0.008X₆。X₁~X₆分别表示使用利尿剂、心血管疾病、肾脏疾病、血流感染、Alb、CrCl。经 ROC 曲线分析验证,模型组 AUC为0.750（95%CI:0.692~0.808, P<0.001）,H-L检验χ²值为7.535,P=0.480;验证组 AUC 为 0.821（95%CI:0.749~0.893, P<0.001）,H-L检验χ²值为13.924,P=0.084,提示该模型具有较好的区分度。模型的约登指数最大值为 0.389,对应ROC 曲线切点最佳值为-0.976,敏感度为56.3%,特异度为82.6%。k折交叉验证提示该模型的准确率较好（Accuracy=0.823）,一致性较低（Kappa=0.191）。结论 CrCl、Alb、血流感染、肾脏疾病、心血管疾病、利尿剂是注射用伏立康唑发生AKI的独立影响因素。基于这6个变量建立AKI的预测模型具有一定的区分度,可在一定程度上辅助临床治疗决策,有利于临床安全用药。

关键词: 伏立康唑, 注射用, 急性肾损伤, 危险因素, 真实世界数据, Logistic 回归, k折交叉验证, 预测模型

Abstract: Objective To establish a prediction model for risk factors of acute kidney injury (AKI) indued by voriconazole for injection and carry out internal and external validation to ensure clinical safety of medication based on real-world data. Methods The medical records of patients who were treated with voriconazole for injection for a minimum of 3 days in our hospital and aged 18 or older between January 1, 2020 and June 30, 2023 were collected. Among them, patients who were discharged before January 1, 2023 were used as the modeling group, and the rest as the validation group. The basic information of patients and such data as the indicators of experimental examinations, results of clinical diagnosis and combined medications was retrieved. Patients were divided into the AKI group and non-AKI group according to the occurrence of AKI. Multivariate logistic regression was used to analyze the risk factors for AKI induced by voriconazole for injection, and a prediction model was established. Discrimination and calibration were evaluated based on the receiver operating characteristic (Receiver Operating Characteristic, ROC) area under the curve (Area Under Curve, AUC) and H-L test (Hosmerand Lemeshow Test). The applicability of the model was evaluated both internally and externally. Results A total of 625 patients (371 males, 254 females) were included in the study. Among them, there were 489 cases in the modeling group (296 males and 193 females), with 87 cases of AKI, compared with 136 cases in the verification group (75 males, 61 females), with 32 cases of AKI. Multivariate logistic regression analysis of the modeling group showed that bloodstream infections, kidney diseases, cardiovascular diseases, and the use of diuretics were risk factors for AKI, while CrCl (Creatinine Clearance) and Alb(Albumin) were protective factors. The AUC of the model group was 0.750 (95%CI: 0.692~0.808, P<0.001) while the H-L test χ² value was 7.535, P=0.480, compared with 0.821(95%CI: 0.749~0.893, P<0.001) and 13.924, P=0.084 in the verification group was, suggesting that the model had good discrimination. The maximum value of the Youden index of the model was 0.389, and the best value corresponding to the tangent point of the ROC curve was -0.976, the sensitivity was 56.3%, and the specificity was 82.6%. k-fold cross-validation suggested that the accuracy of the model was better (0.823) and the consistency was lower (0.191). Conclusion CrCl, Alb, bloodstream infections, kidney diseases, cardiovascular diseases, and diuretics are independent factors for AKI induced by voriconazole for injection. The prediction model of AKI established based on these 6 variables has some discrimination, which can assist clinical treatment and contribute to safe drug use.

Key words: voriconazole, injection, acute kidney injury, risk factors, real world data, Logistic regression, k-fold cross-validation, prediction model

中图分类号:

R994.11
R969

王书波, 焦婷婷, 董洪亮, 王百聆, 李辉. 基于真实世界数据研究注射用伏立康唑致急性肾损伤的危险因素建立预测模型及验证[J]. 中国药物警戒, 2024, 21(5): 567-571.

WANG Shubo, JIAO Tingting, DONG Hongliang, WANG Bailing, LI Hui. A model for prediction of risk factors of acute kidney injury induced by voriconazole for injection based on real-world data[J]. Chinese Journal of Pharmacovigilance, 2024, 21(5): 567-571.

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