Is blood pressure reduction a valid surrogate endpoint for stroke prevention? An analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the Surrogate Threshold Effect (STE) and the Biomarker-Surrogacy (BioSurrogate) Evaluation Schema (BSES)
Is blood pressure reduction a valid surrogate endpoint for stroke prevention? An analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the Surrogate Threshold Effect (STE) and the Biomarker-Surrogacy (BioSurrogate) Evaluation Schema (BSES)
复制标题
DOI：
10.1186/1471-2288-12-27
复制
发表时间：
2012-03-12
影响因子：
4
通讯作者：
Rees, David
中科院分区：
文献类型：
--
作者：
Lassere, Marissa N.;Johnson, Kent R.;Rees, David
背景：血压被认为是一个有效的替代终点的主要例子。本研究的目的是：(1)正式评估收缩压和舒张压降低作为预防中风的替代终点；(2)确定何种血压降低可以预测中风的益处。方法：我们确定了至少持续6个月的随机试验，将任何药物降压治疗与安慰剂或不治疗进行比较，并报告基线血压、试验血压、致命和非致命中风。至少一只手臂中风少于5次的试验被排除在外。变量误差加权最小二乘回归模型将卒中的减少分别作为收缩压降低和舒张压降低的函数。较低的95%预测带用于确定最小收缩压和舒张压差，即替代阈值效应（STE），低于该值将无法预测卒中获益。STE用于产生替代阈值效应比例（STEP），这是一种替代指标，使用生物标志物-替代评估图式（BSES3），将其与r方试验水平关联用于评估血压作为卒中的替代终点。结果：在代表所有抗高血压药物类别的18项合格试验中，假设信度系数为0.9，卒中获益的替代阈值效应为收缩压7.1 mmHg和舒张压2.4 mmHg。试验水平相关性分别为0.41和0.64，收缩压和舒张压的STEP分别为66%和78%。STE和STEP对自变量测量误差的稳健性比r平方试验水平的相关性更强。使用BSES3，假设信度系数为0.9，收缩压为B +级，舒张压为a级卒中预防替代终点。相比之下，使用相同的卒中数据集，无法估计心血管（CV）死亡率或全因死亡率降低的STE，尽管收缩压下CV死亡率的STE接近25 mmHg。结论：在本报告中，我们提供了第一个替代阈值效应（STE）的收缩压和舒张压值。我们认为STEs具有表面效度和内容效度，其计算中包含了试验人群、受试者人群和药物干预人群。我们建议STE和STEP指标提供了另一种评估支持替代终点的证据的方法。我们展示了如果使用生物标志物-替代品评估方案（BSES3）在特定情境评估框架内进行正式评估，如何加强替代品评估，并讨论了我们的血压评估对其他生物标志物和患者报告的仪器与替代品指标和试验设计相关的影响。
Background: Blood pressure is considered to be a leading example of a valid surrogate endpoint. The aims of this study were to (i) formally evaluate systolic and diastolic blood pressure reduction as a surrogate endpoint for stroke prevention and (ii) determine what blood pressure reduction would predict a stroke benefit.Methods: We identified randomised trials of at least six months duration comparing any pharmacologic antihypertensive treatment to placebo or no treatment, and reporting baseline blood pressure, on-trial blood pressure, and fatal and non-fatal stroke. Trials with fewer than five strokes in at least one arm were excluded. Errors-in-variables weighted least squares regression modelled the reduction in stroke as a function of systolic blood pressure reduction and diastolic blood pressure reduction respectively. The lower 95% prediction band was used to determine the minimum systolic blood pressure and diastolic blood pressure difference, the surrogate threshold effect (STE), below which there would be no predicted stroke benefit. The STE was used to generate the surrogate threshold effect proportion (STEP), a surrogacy metric, which with the R-squared trial-level association was used to evaluate blood pressure as a surrogate endpoint for stroke using the Biomarker-Surrogacy Evaluation Schema (BSES3).Results: In 18 qualifying trials representing all pharmacologic drug classes of antihypertensives, assuming a reliability coefficient of 0.9, the surrogate threshold effect for a stroke benefit was 7.1 mmHg for systolic blood pressure and 2.4 mmHg for diastolic blood pressure. The trial-level association was 0.41 and 0.64 and the STEP was 66% and 78% for systolic and diastolic blood pressure respectively. The STE and STEP were more robust to measurement error in the independent variable than R-squared trial-level associations. Using the BSES3, assuming a reliability coefficient of 0.9, systolic blood pressure was a B + grade and diastolic blood pressure was an A grade surrogate endpoint for stroke prevention. In comparison, using the same stroke data sets, no STEs could be estimated for cardiovascular (CV) mortality or all-cause mortality reduction, although the STE for CV mortality approached 25 mmHg for systolic blood pressure.Conclusions: In this report we provide the first surrogate threshold effect (STE) values for systolic and diastolic blood pressure. We suggest the STEs have face and content validity, evidenced by the inclusivity of trial populations, subject populations and pharmacologic intervention populations in their calculation. We propose that the STE and STEP metrics offer another method of evaluating the evidence supporting surrogate endpoints. We demonstrate how surrogacy evaluations are strengthened if formally evaluated within specific-context evaluation frameworks using the Biomarker-Surrogate Evaluation Schema (BSES3), and we discuss the implications of our evaluation of blood pressure on other biomarkers and patient-reported instruments in relation to surrogacy metrics and trial design.