National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA.
Data Tecnica International, Glen Echo, Maryland, USA.
J Med Genet. 2020 May;57(5):331-338. doi: 10.1136/jmedgenet-2019-106283. Epub 2019 Nov 29.
Classical randomisation of clinical trial patients creates a source of genetic variance that may be contributing to the high failure rate seen in neurodegenerative disease trials. Our objective was to quantify genetic difference between randomised trial arms and determine how imbalance can affect trial outcomes.
5851 patients with Parkinson's disease of European ancestry data and two simulated virtual cohorts based on public data were used. Data were resampled at different sizes for 1000 iterations and randomly assigned to the two arms of a simulated trial. False-negative and false-positive rates were estimated using simulated clinical trials, and per cent difference in genetic risk score (GRS) and allele frequency was calculated to quantify variance between arms.
5851 patients with Parkinson's disease (mean (SD) age, 61.02 (12.61) years; 2095 women (35.81%)) as well as simulated patients from virtually created cohorts were used in the study. Approximately 90% of the iterations had at least one statistically significant difference in individual risk SNPs between each trial arm. Approximately 5%-6% of iterations had a statistically significant difference between trial arms in mean GRS. For significant iterations, the average per cent difference for mean GRS between trial arms was 130.87%, 95% CI 120.89 to 140.85 (n=200). Glucocerebrocidase (GBA) gene-only simulations see an average 18.86%, 95% CI 18.01 to 19.71 difference in GRS scores between trial arms (n=50). When adding a drug effect of -0.5 points in MDS-UPDRS per year at n=50, 33.9% of trials resulted in false negatives.
Our data support the hypothesis that within genetically unmatched clinical trials, genetic heterogeneity could confound true therapeutic effects as expected. Clinical trials should undergo pretrial genetic adjustment or, at the minimum, post-trial adjustment and analysis for failed trials.
临床试验中患者的经典随机化产生了遗传变异的来源,这可能是导致神经退行性疾病试验高失败率的原因。我们的目的是量化随机试验组之间的遗传差异,并确定不平衡如何影响试验结果。
使用欧洲裔帕金森病患者的 5851 例数据和基于公共数据的两个模拟虚拟队列。对数据进行了 1000 次迭代的不同大小的重新采样,并随机分配到模拟试验的两个臂中。使用模拟临床试验估计假阴性和假阳性率,并计算遗传风险评分(GRS)和等位基因频率的差异百分比,以量化臂之间的差异。
研究中使用了 5851 例帕金森病患者(平均(SD)年龄,61.02(12.61)岁;2095 名女性(35.81%))以及从虚拟创建队列中获得的模拟患者。大约 90%的迭代在每个试验臂之间的个体风险 SNP 中至少有一个具有统计学意义的差异。大约 5%-6%的迭代在试验臂之间的平均 GRS 存在统计学差异。对于具有统计学意义的迭代,试验臂之间平均 GRS 的平均差异百分比为 130.87%,95%置信区间为 120.89-140.85(n=200)。仅 GBA 基因模拟试验,试验臂之间 GRS 评分的平均差异为 18.86%,95%置信区间为 18.01-19.71(n=50)。当在 n=50 时,在 MDS-UPDRS 中每年添加药物效应-0.5 分时,33.9%的试验导致假阴性。
我们的数据支持以下假设:在遗传上不匹配的临床试验中,遗传异质性可能会干扰预期的真正治疗效果。临床试验应进行预先试验遗传调整,或者至少在试验失败后进行调整和分析。