Xue Shengmin, Lu Haodi, Tang Lian, Fang Jie, Shi Lu, Li Jingjing, Yu Yanxia, Zhou Qin, Xue Sudong
Department of Pharmacy, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou 215002, Jiangsu, China.
Department of Pharmacy, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200025, China. Corresponding author: Tang Lian, Email:
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2020 Jan;32(1):50-55. doi: 10.3760/cma.j.cn121430-20190814-00009.
To estimate the predictive performance of the population pharmacokinetics software JPKD-vancomycin on predicting the vancomycin steady-state trough concentration, and to analyze the related factors affecting the predictive performance.
The clinical data of patients who were treated with vancomycin and received therapeutic drug monitoring (TDM) admitted to Suzhou Hospital Affiliated to Nanjing Medical University from July 2013 to December 2018 were enrolled. All patients were designed an empirical vancomycin regimen (initial regimen) according to vancomycin medication guidelines. Steady-state trough concentrations of vancomycin were determined at 48 hours after the first dose and 0.5 hour before the next dose. Dosage regimen was adjusted when steady-state trough concentration was not in 10-20 mg/L (adjustment regimen), and then the steady-state trough concentration was determined again 48 hours after adjustment. First, the JPKD-vancomycin software was used to calculate the initial regimen and predict the steady-state trough concentration according to the results calculated by classic pharmacokinetic software Vancomycin Calculator. Second, the JPKD-vancomycin software was used to adjust the vancomycin dosage regime and predict the steady-state trough concentration of adjustment regimen. The weight residual (WRES) between the predicted steady-state trough concentration (C) and the measured steady-state trough concentration (C) was used to evaluate the ability of the JPKD-vancomycin software for predicting the vancomycin steady-state trough concentration. The TDM results of initial regimen were divided into accurate prediction group (WRES < 30%) and the inaccurate prediction group (WRES ≥ 30%) according to the WRES value. Patient and disease characteristics including gender, age, weight, height, the length of hospital stay, comorbidities, vasoactive agent, mechanical ventilation, smoking history, postoperative, obstetric patients, trauma, laboratory indicators, vancomycin therapy and TDM results were collected from electronic medical records. Univariate and multivariate Logistic regression analysis was used to screen the related factors that influence the predictive performance of JPKD-vancomycin software, and the receiver operating characteristic (ROC) curve was drawn to evaluate its predictive value.
A total of 310 patients were enrolled, and 467 steady-state trough concentrations of vancomycin were collected, including 310 concentrations of initial regimen and 157 concentrations of adjustment regimen. Compared with the initial regimen, the WRES of adjusted regimen was significantly reduced [14.84 (6.05,22.89)% vs. 20.41 (11.06,45.76)%, P < 0.01], and the proportion of WRES < 30% increased significantly [82.80% (130/157) vs. 63.87% (198/310), P < 0.01]. These results indicated that JPKD-vancomycin software had a better accuracy prediction for steady-state trough concentration of the adjusted regimen than the initial regimen. There were 198 concentrations in the accurate prediction group and 112 in the inaccurate prediction group. Univariate Logistic regression analysis showed that women [odds ratio (OR) = 0.466, 95% confidence interval (95%CI) was 0.290-0.746, P = 0.002], low body weight (OR = 0.974, 95%CI was 0.953-0.996, P = 0.022), short height (OR = 0.963, 95%CI was 0.935-0.992, P = 0.014), low vancomycin clearance (CL; OR < 0.001, 95%CI was 0.000-0.231, P = 0.023) and postoperative patients (OR = 1.695, 95%CI was 1.063-2.702, P = 0.027) were related factors affecting the predictive performance of JPKD-vancomycin software. Multivariate Logistic regression analysis indicated that women (OR = 0.449, 95%CI was 0.205-0.986, P = 0.046), low CL (OR < 0.001, 95%CI was 0.000-0.081, P = 0.015) and postoperative patients (OR = 2.493, 95%CI was 1.455-4.272, P = 0.001) were independent risk factors for inaccurate prediction of JPKD-vancomycin software. The ROC analysis indicated that the area under ROC curve (AUC) of the CL for evaluating the accuracy of JPKD-vancomycin software in predicting vancomycin steady-state trough concentration was 0.571, the sensitivity was 56.3%, and the specificity was 57.1%. The predictive performance of JPKD-vancomycin software was decreased when CL was lower than 0.065 L×h×kg.
JPKD-vancomycin software had a better predictive performance for the vancomycin steady-state trough concentrations of adjustment regimen than initial regimen. JPKD-vancomycin software had a poor predictive performance when the patient was female, having low CL, and was postoperative. The predictive performance of JPKD-vancomycin software was decreased when CL was lower than 0.065 L×h×kg.
评估群体药代动力学软件JPKD - 万古霉素预测万古霉素稳态谷浓度的性能,并分析影响其预测性能的相关因素。
纳入2013年7月至2018年12月在南京医科大学附属苏州医院接受万古霉素治疗并进行治疗药物监测(TDM)的患者临床资料。所有患者均根据万古霉素用药指南制定经验性万古霉素给药方案(初始方案)。在首剂给药后48小时及下次给药前0.5小时测定万古霉素稳态谷浓度。当稳态谷浓度不在10 - 20 mg/L时调整给药方案(调整方案),调整后48小时再次测定稳态谷浓度。首先,使用JPKD - 万古霉素软件根据经典药代动力学软件万古霉素计算器计算的结果计算初始方案并预测稳态谷浓度。其次,使用JPKD - 万古霉素软件调整万古霉素给药方案并预测调整方案的稳态谷浓度。用预测的稳态谷浓度(C)与实测的稳态谷浓度(C)之间的权重残差(WRES)评估JPKD - 万古霉素软件预测万古霉素稳态谷浓度的能力。根据WRES值将初始方案的TDM结果分为准确预测组(WRES < 30%)和不准确预测组(WRES≥30%)。从电子病历中收集患者和疾病特征,包括性别、年龄、体重、身高、住院时间、合并症、血管活性药物使用情况、机械通气、吸烟史、术后情况、产科患者、创伤、实验室指标、万古霉素治疗情况及TDM结果。采用单因素和多因素Logistic回归分析筛选影响JPKD - 万古霉素软件预测性能的相关因素,并绘制受试者工作特征(ROC)曲线评估其预测价值。
共纳入310例患者,收集到467个万古霉素稳态谷浓度,其中初始方案浓度310个,调整方案浓度157个。与初始方案相比,调整方案的WRES显著降低[14.84(6.05,22.89)% vs. 20.41(11.06,45.76)%,P < 0.01],WRES < 30%的比例显著增加[82.80%(130/157)vs. 63.87%(198/310),P < 0.01]。这些结果表明,JPKD - 万古霉素软件对调整方案稳态谷浓度的预测准确性优于初始方案。准确预测组有198个浓度,不准确预测组有112个浓度。单因素Logistic回归分析显示,女性[比值比(OR) = 0.466,95%置信区间(95%CI)为0.290 - 0.746,P = 0.002]、低体重(OR = 0.974,95%CI为0.953 - 0.996,P = 0.022)、矮身高(OR = 0.963,95%CI为0.935 - 0.992,P = 0.014)、低万古霉素清除率(CL;OR < 0.001,95%CI为0.000 - 0.231,P = 0.023)及术后患者(OR = 1.695,95%CI为1.063 - 2.702,P = 0.027)是影响JPKD - 万古霉素软件预测性能的相关因素。多因素Logistic回归分析表明,女性(OR = 0.449, 95%CI为0.205 - 0.986,P = 0.046)、低CL(OR < 0.001,95%CI为0.000 - 0.081,P = 0.015)及术后患者(OR = 2.493,95%CI为1.455 - 4.272,P = 0.001)是JPKD - 万古霉素软件预测不准确的独立危险因素。ROC分析表明,用于评估JPKD - 万古霉素软件预测万古霉素稳态谷浓度准确性的CL的ROC曲线下面积(AUC)为0.571,灵敏度为56.3%,特异度为57.1%。当CL低于0.065 L×h×kg时,JPKD - 万古霉素软件的预测性能下降。
JPKD - 万古霉素软件对调整方案万古霉素稳态谷浓度的预测性能优于初始方案。当患者为女性、CL低及术后时,JPKD - 万古霉素软件的预测性能较差。当CL低于0.065 L×h×kg时,JPKD - 万古霉素软件的预测性能下降。