Unit of Clinical Pharmacology, Luigi Sacco University Hospital, via GB Grassi 74, 20157 Milano, Italy.
J Clin Pharmacol. 2012 Mar;52(3):440-5. doi: 10.1177/0091270010395939. Epub 2011 Mar 7.
Stepwise multiple regression analyses were applied to 50 raltegravir pharmacokinetic profiles from 50 HIV patients with the goal to identify limited sampling strategies for the prediction of drug area under the time-concentration curve (AUC(0-12)). Raltegravir single sampling point-based equations failed to reliably predict daily drug exposure. Conversely, different algorithms based on few samples and associated with good correlation, acceptable bias, and imprecision with the measured raltegravir AUC(0-12) were identified. These models could used to predict raltegravir exposure for clinic or research purposes.
逐步多元回归分析应用于 50 例 HIV 患者的 50 份雷替拉韦药代动力学曲线，旨在确定有限采样策略以预测药物时间-浓度曲线下面积（AUC（0-12））。雷替拉韦单点采样的方程无法可靠地预测每日药物暴露量。相反，基于少量样本的不同算法与良好的相关性、可接受的偏差和对雷替拉韦 AUC（0-12）的测量不精确性相关，这些模型可用于预测雷替拉韦的临床或研究暴露量。
