Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein-Zuid 10, 6500 HB, Nijmegen, The Netherlands.
Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Eur J Clin Pharmacol. 2021 May;77(5):727-733. doi: 10.1007/s00228-020-03042-4. Epub 2020 Nov 18.
An influential covariate for pharmacokinetics is (body) size. Recently, the method of estimation of normal fat mass (NFM) has been advocated. Here, the relative contribution of fat mass, estimated as a fraction fat (Ffat), is used to explain differences in pharmacokinetic parameters. This concept is more and more applied. However, it remains unclear whether NFM can be reliably estimated in these typical studies.
We performed an evaluation of the reliability of NFM estimation in a typical study size (n = 30), otherwise best-case scenario, by means of a pharmacokinetic simulation study. Several values of Ffat were investigated.
In a typical pharmacokinetic study, high imprecision was observed for NFM parameter estimates over a range of scenarios. For example, in a scenario where the true value of Ffat on clearance was 0.5, we found a 95% confidence interval of - 0.1 to 2.1, demonstrating a low precision. The implications for practice are that one could conclude that fat-free mass best describes the relationship of the pharmacokinetics with body size, while the true relationship was between fat-free mass and total body weight. Consequently, this could lead to incorrect extrapolation of pharmacokinetics to extreme body sizes.
In typical pharmacokinetic studies, NFM should be used with caution because the Ffat estimates have low precision. The estimation of Ffat should always be preceded by careful study design evaluation before planning a study, to ensure that the design and sample size is sufficient to apply this potentially useful methodology.
对药代动力学有重要影响的一个协变量是（身体）大小。最近，人们提倡使用正常脂肪量（NFM）的估计方法。在这里，脂肪量的相对贡献（估计为脂肪分数 Ffat）被用来解释药代动力学参数的差异。这个概念越来越多地被应用。然而，在这些典型研究中，NFM 是否可以可靠地估计仍然不清楚。
我们通过药代动力学模拟研究，对典型研究规模（n = 30）的 NFM 估计的可靠性进行了评估，这是最好的情况。研究考察了几个 Ffat 值。
在典型的药代动力学研究中，在一系列情况下，NFM 参数估计的精度都很差。例如，在 Ffat 对清除率的真实值为 0.5 的情况下，我们发现 95%置信区间为 -0.1 至 2.1，表明精度低。这对实践的影响是，人们可能会得出结论，认为去脂体重最能描述药代动力学与身体大小的关系，而真实的关系是去脂体重与总体重之间的关系。因此，这可能导致药代动力学在极端身体大小上的不正确外推。
在典型的药代动力学研究中，应该谨慎使用 NFM，因为 Ffat 的估计精度较低。在计划研究之前，应始终在仔细研究设计评估之后进行 Ffat 的估计，以确保设计和样本量足以应用这种潜在有用的方法。
