轻度卒中后1年以脑白质高信号进展作为中间结局的试验样本量考量：一项前瞻性队列研究的结果
Sample size considerations for trials using cerebral white matter hyperintensity progression as an intermediate outcome at 1 year after mild stroke: results of a prospective cohort study.
作者信息
Chappell Francesca M, Del Carmen Valdés Hernández Maria, Makin Stephen D, Shuler Kirsten, Sakka Eleni, Dennis Martin S, Armitage Paul A, Muñoz Maniega Susana, Wardlaw Joanna M
机构信息
Neuroimaging Sciences, Centre for Clinical Brain Sciences (CCBS) FU303e, The University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Academic Unit of Radiology, University of Sheffield, C Floor, Royal Hallamshire Hospital, Sheffield, S10 2JF, UK.
出版信息
Trials. 2017 Feb 21;18(1):78. doi: 10.1186/s13063-017-1825-7.
BACKGROUND
White matter hyperintensities (WMHs) are commonly seen on in brain imaging and are associated with stroke and cognitive decline. Therefore, they may provide a relevant intermediate outcome in clinical trials. WMH can be measured as a volume or visually on the Fazekas scale. We investigated predictors of WMH progression and design of efficient studies using WMH volume and Fazekas score as an intermediate outcome.
METHODS
We prospectively recruited 264 patients with mild ischaemic stroke and measured WMH volume, Fazekas score, age and cardiovascular risk factors at baseline and 1 year. We modelled predictors of WMH burden at 1 year and used the results in sample size calculations for hypothetical randomised controlled trials with different analysis plans and lengths of follow-up.
RESULTS
Follow-up WMH volume was predicted by baseline WMH: a 0.73-ml (95% CI 0.65-0.80, p < 0.0001) increase per 1-ml baseline volume increment, and a 2.93-ml increase (95% CI 1.76-4.10, p < 0.0001) per point on the Fazekas scale. Using a mean difference of 1 ml in WMH volume between treatment groups, 80% power and 5% alpha, adjusting for all predictors and 2-year follow-up produced the smallest sample size (n = 642). Other study designs produced samples sizes from 2054 to 21,270. Sample size calculations using Fazekas score as an outcome with the same power and alpha, as well as an OR corresponding to a 1-ml difference, were sensitive to assumptions and ranged from 2504 to 18,886.
CONCLUSIONS
Baseline WMH volume and Fazekas score predicted follow-up WMH volume. Study size was smallest using volumes and longer-term follow-up, but this must be balanced against resources required to measure volumes versus Fazekas scores, bias due to dropout and scanner drift. Samples sizes based on Fazekas scores may be best estimated with simulation studies.
背景
脑白质高信号（WMHs）在脑成像中常见，与中风和认知衰退相关。因此，它们可能在临床试验中提供一个相关的中间结果。WMH可以作为体积来测量，也可以通过Fazekas量表进行视觉评估。我们研究了WMH进展的预测因素，并设计了以WMH体积和Fazekas评分作为中间结果的高效研究。
方法
我们前瞻性招募了264例轻度缺血性中风患者，在基线和1年时测量WMH体积、Fazekas评分、年龄和心血管危险因素。我们对1年时WMH负担的预测因素进行建模，并将结果用于不同分析计划和随访时长的假设随机对照试验的样本量计算。
结果
随访时的WMH体积可由基线WMH预测：基线体积每增加1 ml，增加0.73 ml（95%CI 0.65 - 0.80，p < 0.0001），Fazekas量表每增加1分，增加2.93 ml（95%CI 1.76 - 4.10，p < 0.0001）。使用治疗组间WMH体积平均差异为1 ml、检验效能为80%和α为5%，对所有预测因素进行校正并进行2年随访时样本量最小（n = 642）。其他研究设计的样本量从2054到21270不等。以Fazekas评分为结果，在相同效能和α以及对应1 ml差异的OR情况下进行样本量计算，对假设敏感，范围为2504到18886。
结论
基线WMH体积和Fazekas评分可预测随访时的WMH体积。使用体积和长期随访时研究规模最小，但这必须与测量体积和Fazekas评分所需的资源、失访和扫描仪漂移导致的偏倚相平衡。基于Fazekas评分的样本量可能最好通过模拟研究来估计。
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