Department of Radiation Oncology and Center for Systems Biology, The Cancer Institute of New Jersey, New Brunswick, NJ 08901, USA.
BMC Med Res Methodol. 2013 Jun 12;13:77. doi: 10.1186/1471-2288-13-77.
Drug interactions can have a significant impact on the response to combinatorial therapy for anticancer treatment. In some instances these interactions can be anticipated based on pre-clinical models. However, the anticipation of drug interactions in the clinical context is in general a challenging task.
Here we propose the pooled analysis of clinical trials as a mean to investigate drug interactions in anticancer therapy. To this end we collected 1,163 Phase II clinical trials with response data on over 53,745 subjects.
We provide statistical definitions of drugs resulting in clinical synergy and antagonism and identify drug combinations in each group. We also quantify the possibility of inferring interactions between three or more drugs from parameters characterizing the action of single and two-drugs combinations.
Our analysis provides a statistical methodology to track the performance of drug combinations in anticancer therapy and to quantify drug interactions in the clinical context.
药物相互作用会对癌症联合治疗的反应产生重大影响。在某些情况下,这些相互作用可以根据临床前模型来预测。然而,在临床环境中预测药物相互作用通常是一项具有挑战性的任务。
在这里,我们提出将临床试验的汇总分析作为一种研究抗癌治疗中药物相互作用的方法。为此,我们收集了 1163 项具有超过 53745 名受试者的反应数据的 II 期临床试验。
我们提供了导致临床协同和拮抗作用的药物的统计定义,并确定了每组中的药物组合。我们还量化了从表征单药和两药组合作用的参数推断三种或更多药物之间相互作用的可能性。
我们的分析提供了一种统计方法来跟踪抗癌治疗中药物组合的性能,并量化临床环境中的药物相互作用。