School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland.
Community Pharmacy, Department of Ambulatory Care and Community Medicine, University of Lausanne, Lausanne, Switzerland.
Clin Pharmacokinet. 2018 Jan;57(1):1-6. doi: 10.1007/s40262-017-0571-z.
The emergence of oral targeted anticancer agents transformed several cancers into chronic conditions with a need for long-term oral treatment. Although cancer is a life-threatening condition, oncology medication adherence-the extent to which a patient follows the drug regimen that is intended by the prescriber-can be suboptimal in the long term, as in any other chronic disease. Poor adherence can impact negatively on clinical outcomes, notably because most of these drugs are given as a standard non-individualized dosage despite marked inter-individual variabilities that can lead to toxic or inefficacious drug concentrations. This has been especially studied with the prototypal drug imatinib. In the context of therapeutic drug monitoring (TDM), increasingly advocated for oral anticancer treatment optimization, unreported suboptimal adherence affecting drug intake history may lead to significant bias in the concentration interpretation and inappropriate dosage adjustments. In the same way, suboptimal adherence may also bias the results of pharmacokinetic modeling studies, which will affect in turn Bayesian TDM interpretation that relies on such population models. Detailed knowledge of the influence of adherence on plasma concentrations in pharmacokinetic studies or in routine TDM programs is however presently missing in the oncology field. Studies on this topic are therefore eagerly awaited to better pilot the treatment of cancer with the new targeted agents and to find their optimal dosage regimen. Hence, the development and assessment of effective medication adherence programs are warranted for these treatments.
口服靶向抗癌药物的出现使几种癌症转变为需要长期口服治疗的慢性疾病。虽然癌症是一种危及生命的疾病，但与其他任何慢性疾病一样，肿瘤患者的药物依从性（即患者遵循医生规定的药物治疗方案的程度）可能长期不佳。药物依从性差会对临床结果产生负面影响，尤其是因为这些药物大多数都是按照标准的非个体化剂量给药，尽管存在明显的个体间差异，可能导致药物浓度有毒或无效。这在原型药物伊马替尼的研究中尤为明显。在治疗药物监测（TDM）的背景下，越来越提倡优化口服抗癌治疗，未报告的药物依从性不佳会影响药物摄入史，从而导致对浓度解读的显著偏差和不适当的剂量调整。同样，药物依从性不佳也可能会影响药代动力学建模研究的结果，进而影响依赖于这些人群模型的贝叶斯 TDM 解读。然而，目前在肿瘤学领域中，尚缺乏关于药物依从性对药代动力学研究或常规 TDM 方案中血浆浓度影响的详细了解。因此，迫切需要开展关于该主题的研究，以更好地指导新型靶向药物治疗癌症，并找到最佳的剂量方案。因此，这些治疗方法需要开发和评估有效的药物依从性计划。
