Odette Cancer Centre, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, ON, M4N 3M5, Canada.
Department of Public Health Sciences, Canadian Cancer Trials Group, Queen's, University, Kingston, ON, Canada.
BMC Med Res Methodol. 2023 Aug 3;23(1):179. doi: 10.1186/s12874-023-01956-y.
Historically, a priori power and sample size calculations have not been routinely performed cost-effectiveness analyses (CEA), partly because the absence of published cost and effectiveness correlation and variance data, which are essential for power and sample size calculations. Importantly, the empirical correlation between cost and effectiveness has not been examined with respect to the estimation of value-for-money in clinical literature. Therefore, it is not well established if cost-effectiveness studies embedded within randomized-controlled-trials (RCTs) are under- or over-powered to detect changes in value-for-money. However, recently guidelines (such as those from ISPOR) and funding agencies have suggested sample size and power calculations should be considered in CEAs embedded in clinical trials.
We examined all RCTs conducted by the Canadian Cancer Trials Group with an embedded cost-effectiveness analysis. Variance and correlation of effectiveness and costs were derived from original-trial data. The incremental net benefit method was used to calculate the power of the cost-effectiveness analysis, with exploration of alternative correlation and willingness-to-pay values.
We identified four trials for inclusion. We observed that a hypothetical scenario of correlation coefficient of zero between cost and effectiveness led to a conservative estimate of sample size. The cost-effectiveness analysis was under-powered to detect changes in value-for-money in two trials, at willingness-to-pay of $100,000. Based on our observations, we present six considerations for future economic evaluations, and an online program to help analysts include a priori sample size and power calculations in future clinical trials.
The correlation between cost and effectiveness had a potentially meaningful impact on the power and variance of value-for-money estimates in the examined cost-effectiveness analyses. Therefore, the six considerations and online program, may facilitate a priori power calculations in embedded cost-effectiveness analyses in future clinical trials.
历史上,由于缺乏发表的成本和效果相关性和方差数据,这对于进行功效和样本量计算是至关重要的,因此,在进行成本效益分析(CEA)时,通常不会进行先验功效和样本量计算。重要的是,在临床文献中,尚未根据价值的估计来检验成本效益的经验相关性。因此,在随机对照试验(RCT)中嵌入的成本效益研究是否能够检测到价值变化尚不清楚。但是,最近的指南(例如 ISPOR 指南)和资助机构建议在临床试验中嵌入的 CEAs 中应考虑样本量和功效计算。
我们检查了加拿大癌症试验组进行的所有嵌入成本效益分析的 RCT。从原始试验数据中得出了效果和成本的方差和相关性。使用增量净效益方法计算成本效益分析的功效,并探索了替代相关性和意愿支付值。
我们确定了四个试验进行了纳入分析。我们观察到,成本和效果之间的相关系数为零的假设情况导致样本量的保守估计。在两个试验中,在支付意愿为 100,000 美元的情况下,成本效益分析无法检测到价值变化。根据我们的观察结果,我们为未来的经济评估提出了六点考虑因素,并提供了一个在线程序,以帮助分析师在未来的临床试验中进行先验样本量和功效计算。
在检查的成本效益分析中,成本与效果之间的相关性对价值估计的功效和方差具有潜在的重要影响。因此,这六点考虑因素和在线程序可能有助于在未来的临床试验中嵌入成本效益分析的先验功效计算。