Stein U, Oellerich M, Sybrecht G W, Schneider B
Institut für Klinische Chemie, Medizinische Hochschule Hannover, Federal Republic of Germany.
J Clin Chem Clin Biochem. 1988 Jun;26(6):405-14. doi: 10.1515/cclm.1988.26.6.405.
A novel Bayesian drug dosing program (Abbott Pharmacokinetic Systems, Theophylline Program) was evaluated. The predictive accuracy of this method was assessed in 10 healthy volunteers receiving single intravenous test doses. Estimates for clearance and distribution volume were compared with those obtained from the area under the curve. The observed prediction error depended largely on sampling time. The deviations were lowest for the distribution volume during the first 60 min and for clearance at 12 hours after theophylline administration. Furthermore the Bayesian technique was prospectively evaluated in 10 hospitalized and 22 outpatients treated with sustained-release theophylline preparations (Uniphyllin, Bronchoretard, PulmiDur). Predictive precision and accuracy were adequate, if theophylline was given twice daily. The highest predictive accuracy was achieved in outpatients, if predictions were based on trough concentrations. In 19/22 outpatients prediction errors were within a clinically acceptable range (mean prediction error +/- standard deviation; -0.6 +/- 2.1 mg/l). Moreover in hospitalized patients (n = 5) with twice-daily maintenance regimens, concentration-time curves could mainly be predicted with sufficient accuracy. Hospitalized patients (n = 5) with once-daily dosing showed large fluctuations between peak and trough theophylline concentrations in serum. In these patients a reliable prediction of the concentration-time curves was not possible apparently due to non-linearity of theophylline kinetics. Relatively large prediction errors were found in one patient with acute viral respiratory illness and 3 patients with altered absorption. Despite certain limitations the clinical application of the Bayesian forecasting method tested appears to be promising.
对一种新型贝叶斯给药程序(雅培药代动力学系统,茶碱程序)进行了评估。在10名接受单次静脉注射试验剂量的健康志愿者中评估了该方法的预测准确性。将清除率和分布容积的估计值与从曲线下面积获得的估计值进行比较。观察到的预测误差很大程度上取决于采样时间。在茶碱给药后最初60分钟内,分布容积的偏差最小,在12小时时清除率的偏差最小。此外,对10名住院患者和22名接受缓释茶碱制剂(优喘平、博利康尼缓释片、普米杜尔)治疗的门诊患者进行了贝叶斯技术的前瞻性评估。如果每天给予两次茶碱,预测精度和准确性是足够的。如果根据谷浓度进行预测,门诊患者的预测准确性最高。在22名门诊患者中,19名的预测误差在临床可接受范围内(平均预测误差±标准差;-0.6±2.1mg/L)。此外,在接受每日两次维持治疗方案的住院患者(n = 5)中,浓度-时间曲线主要可以得到足够准确的预测。接受每日一次给药的住院患者(n = 5)血清中茶碱峰浓度和谷浓度之间波动较大。在这些患者中,由于茶碱动力学的非线性,显然无法可靠地预测浓度-时间曲线。在1名急性病毒性呼吸道疾病患者和3名吸收改变的患者中发现了相对较大的预测误差。尽管存在某些局限性,但所测试的贝叶斯预测方法在临床应用中似乎很有前景。