Model-Based Optimisation of Deferoxamine Chelation Therapy.
Model-Based Optimisation of Deferoxamine Chelation Therapy.
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DOI：
10.1007/s11095-015-1805-0
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发表时间：
2016-02
影响因子：
3.7
通讯作者：
Della Pasqua O
中科院分区：
文献类型：
--
作者：
Bellanti F;Del Vecchio GC;Putti MC;Cosmi C;Fotzi I;Bakshi SD;Danhof M;Della Pasqua O
在这里，我们展示了如何使用基于模型的方法来进一步了解临床和人口统计学协变量对铁过载进展的作用。去铁胺的治疗效果用于说明疾病建模作为表征个体患者治疗反应的手段的应用。本分析使用了27例重型β地中海贫血患者的血清铁蛋白、人口统计学特征和临床常规实践中的个体治疗数据。血清铁蛋白的时间过程由分层非线性混合效应模型描述，其中依从性作为协变量因子进行参数化。在NONMEM（7.2.0）中执行建模和模拟程序。周转模型最好地描述了血清铁蛋白随时间的变化，输血对铁蛋白转化率的影响和去铁胺对消除参数（Kout）的影响成比例。模拟结果表明，执行质量差优于休药期;并且与依从性模式无关，如果错过>60%的剂量，则治疗干预无效。铁蛋白反应的建模使得能够表征由于慢性输血导致的铁过载的动力学。该方法可用于支持临床实践中的决策，包括现有和新型螯合剂的剂量个性化。本文的在线版本（doi：10.1007/s11095-015-1805-0）包含补充材料，可供授权用户使用。
Here we show how a model-based approach may be used to provide further insight into the role of clinical and demographic covariates on the progression of iron overload. The therapeutic effect of deferoxamine is used to illustrate the application of disease modelling as a means to characterising treatment response in individual patients. Serum ferritin, demographic characteristics and individual treatment data from clinical routine practice on 27 patients affected by β-thalassaemia major were used for the purposes of this analysis. The time course of serum ferritin was described by a hierarchical nonlinear mixed effects model, in which compliance was parameterised as a covariate factor. Modelling and simulation procedures were implemented in NONMEM (7.2.0). A turnover model best described serum ferritin changes over time, with the effect of blood transfusions introduced on the ferritin conversion rate and the effect of deferoxamine on the elimination parameter (Kout) in a proportional manner. The results of the simulations showed that poor quality of execution is preferable over drug holidays; and that independently of the compliance pattern, the therapeutic intervention is not effective if >60% of the doses are missed. Modelling of ferritin response enables characterisation of the dynamics of iron overload due to chronic transfusion. The approach can be used to support decision making in clinical practice, including personalisation of the dose for existing and novel chelating agents. The online version of this article (doi:10.1007/s11095-015-1805-0) contains supplementary material, which is available to authorised users.