Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.
Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.
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DOI：
10.1186/s12874-018-0475-0
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发表时间：
2018-02-08
影响因子：
4
通讯作者：
Stallard N
中科院分区：
文献类型：
--
作者：
Pearce M;Hee SW;Madan J;Posch M;Day S;Miller F;Zohar S;Stallard N
大多数验证性随机对照临床试验 (RCT) 均设计有指定功效，通常为 80% 或 90%，用于在给定显着性水平（通常为 2.5%）进行单方面检验的假设检验。监管机构对实验性治疗的批准是基于这种显着性检验的结果和其他信息，以平衡不良事件的风险与治疗对未来患者的益处。在罕见疾病的情况下，招募足够的患者以达到临床合理效应大小的常规错误率可能是不可行的，这表明决策过程应反映目标人群的规模。我们考虑使用决策理论信息值（VOI）方法来获得一系列设置中验证性随机对照试验的最佳样本量和显着性水平。我们假设决策者代表社会。为简单起见，我们假设主要终点呈正态分布，均值未知，遵循一些正态先验分布，代表试验前可用疗法的预期有效性信息。该方法通过在血友病 A 的随机对照试验中的应用来说明。我们明确指定了在改善主要结局方面的效用，并将其与试验期间和未来的治疗患者的成本（包括财务费用和潜在危害）进行比较。临床试验的最佳样本量随着人群规模的减少而减少。对于治疗未来患者的非零成本，无论是金钱还是潜在的有害影响，随着人口规模的增加，需要更有力的证据来批准，但如果忽略治疗未来患者的成本，则情况并非如此。决策理论 VOI 方法提供了一种灵活的方法，具有 I 类错误率和功效（或等效的试验样本量），具体取决于正在研究的治疗的未来人群的规模。当有大量关于患者群体的信息时，这可能特别适合小群体。本文的在线版本 (10.1186/s12874-018-0475-0) 包含补充材料，可供授权用户使用。
Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population. We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future. The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored. Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population. The online version of this article (10.1186/s12874-018-0475-0) contains supplementary material, which is available to authorized users.
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影响因子：
2.3
作者：
Hee SW;Hamborg T;Day S;Madan J;Miller F;Posch M;Zohar S;Stallard N
通讯作者：
Stallard N
影响因子：
3.7
作者：
LEWIS, RJ;BERRY, DA
通讯作者：
BERRY, DA
影响因子：
2
作者：
Hampson, Lisa V.;Whitehead, John;Eleftheriou, Despina;Brogan, Paul
通讯作者：
Brogan, Paul
DOI：
10.1016/s0197-2456(97)00098-6
发表时间：
1998-04-01
期刊：
CONTROLLED CLINICAL TRIALS
影响因子：
--
作者：
Hornberger, J;Eghtesady, P
通讯作者：
Eghtesady, P
影响因子：
2.7
作者：
Chen, Maggie H.;Willan, Andrew R.
通讯作者：
Willan, Andrew R.