Background

A fundamental concept in pharmacology is that increasing dose increases drug effect. This is the basis of anaesthetic titration: the dose is increased when increased drug effect is desired and decreased when reduced drug effect is desired. In the setting of titration, the correlation of doses and observed drug effects can be negative, for example increasing dose reduces drug effect. We have termed this the drug titration paradox. We hypothesised that this could be explained, at least in part, by intrasubject variability. If the drug titration paradox is simply an artifact of pooling population data, then a mixed-effects analysis that accounts for interindividual variability in drug sensitivity should ‘flip’ the observed correlation, such that increasing dose increases drug effect.

Methods

We tested whether a mixed-effects analysis could correctly reveal the underlying pharmacology using previously published data obtained during automatic feedback control of mean arterial pressure (MAP) with alfentanil (effect site concentration, Ce_Alf) during surgery. The relationship between MAP and Ce_Alf was explored with linear regression and a linear mixed-effects model.

Results

A linear mixed-effects model did not identify the correct underlying pharmacology because of the presence of the titration paradox in the individual data.

Conclusions

The relationship between drug dose and drug effect must be determined under carefully controlled experimental conditions. In routine care, where the effect is profoundly influenced by varying clinical conditions and drugs are titrated to achieve the desired effect, it is nearly impossible to draw meaningful conclusions about the relationship between dose and effect.

中文翻译：

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药物滴定悖论：更多的药物与个体临床数据中的更多效果无关

背景

药理学的一个基本概念是增加剂量会增加药效。这是麻醉剂滴定的基础：当需要增加药效时增加剂量，当需要降低药效时减少剂量。在滴定的情况下，剂量与观察到的药物作用的相关性可能是负的，例如增加剂量会降低药物作用。我们将其称为药物滴定悖论。我们假设这至少可以部分地由主体内变异性来解释。如果药物滴定悖论只是汇集人口数据的产物，那么考虑药物敏感性个体间差异的混合效应分析应该“翻转”观察到的相关性，这样增加剂量会增加药物效应。

方法

我们使用手术期间使用阿芬太尼（效应部位浓度，Ce _Alf ）自动反馈控制平均动脉压 (MAP) 期间获得的先前公布的数据，测试了混合效应分析是否可以正确揭示潜在的药理学。_{MAP 和 Ce Alf}之间的关系通过线性回归和线性混合效应模型进行了探索。

结果

由于单个数据中存在滴定悖论，线性混合效应模型无法确定正确的潜在药理学。

结论

药物剂量和药效之间的关系必须在仔细控制的实验条件下确定。在常规护理中，效果受到不同临床条件的深刻影响，药物滴定以达到预期效果，几乎不可能就剂量和效果之间的关系得出有意义的结论。