INSERM, IAME, Université de Paris, Paris, France.
Clinical Research, Biostatistics and Epidemiology Department, AP-HP, Hôpital Bichat, Paris, France.
CPT Pharmacometrics Syst Pharmacol. 2021 Apr;10(4):340-349. doi: 10.1002/psp4.12624.
Gene-treatment interactions, just like drug-drug interactions, can have dramatic effects on a patient response and therefore influence the clinician decision at the patient's bedside. Crossover designs, although they are known to decrease the number of subjects in drug-interaction studies, are seldom used in pharmacogenetic studies. We propose to evaluate, via realistic clinical trial simulations, to what extent crossover designs can help quantifying the gene-treatment interaction effect. We explored different scenarios of crossover and parallel design studies comparing two symptom-modifying treatments in a chronic and stable disease accounting for the impact of a one gene and one gene-treatment interaction. We varied the number of subjects, the between and within subject variabilities, the gene polymorphism frequency and the effect sizes of the treatment, gene, and gene-treatment interaction. Each simulated dataset was analyzed using three models: (i) estimating only the treatment effect, (ii) estimating the treatment and the gene effects, and (iii) estimating the treatment, the gene, and the gene-treatment interaction effects. We showed how ignoring the gene-treatment interaction results in the wrong treatment effect estimates. We also highlighted how crossover studies are more powerful to detect a treatment effect in the presence of a gene-treatment interaction and more often lead to correct treatment attribution.
基因-治疗相互作用与药物-药物相互作用一样，可能对患者的反应产生巨大影响，从而影响临床医生在患者床边的决策。交叉设计虽然已知可以减少药物相互作用研究中的受试者数量，但在药物遗传学研究中很少使用。我们建议通过现实的临床试验模拟来评估交叉设计在多大程度上可以帮助量化基因-治疗相互作用效应。我们探讨了交叉和平行设计研究的不同情况，比较了慢性和稳定疾病中两种症状改善治疗方法，考虑了一个基因和一个基因-治疗相互作用的影响。我们改变了受试者数量、个体内和个体间的变异性、基因多态性频率以及治疗、基因和基因-治疗相互作用的效果大小。每个模拟数据集都使用三种模型进行分析：（i）仅估计治疗效果，（ii）估计治疗和基因效果，以及（iii）估计治疗、基因和基因-治疗相互作用效果。我们展示了忽略基因-治疗相互作用如何导致错误的治疗效果估计。我们还强调了交叉研究在存在基因-治疗相互作用的情况下更有能力检测治疗效果，并且更经常导致正确的治疗归因。
