论文标题
通过推断权力来制定药物开发决策
Decision Making in Drug Development via Inference on Power
论文作者
论文摘要
通过在外部研究中观察到的功能中的未知人口级数量来实现典型的功率计算。许多作者和从业者将其视为权力的假定价值，并提供了成功或保证的贝叶斯数量概率。该主张是通过对先前或后验分布进行平均，成功的概率通过捕获未知的真实治疗效果和任何其他种群级参数的不确定性来超越权力。我们使用p值函数来构架成功计算的概率和典型的功率计算，只是产生了两个不同的功率估计值。我们证明，基于权力的任一点估计的执行/不进行决策都不能充分量化和控制所涉及的风险，而是我们主张使用推断权力来改善风险管理和决策的行为。
A typical power calculation is performed by replacing unknown population-level quantities in the power function with what is observed in external studies. Many authors and practitioners view this as an assumed value of power and offer the Bayesian quantity probability of success or assurance as an alternative. The claim is by averaging over a prior or posterior distribution, probability of success transcends power by capturing the uncertainty around the unknown true treatment effect and any other population-level parameters. We use p-value functions to frame both the probability of success calculation and the typical power calculation as merely producing two different point estimates of power. We demonstrate that Go/No-Go decisions based on either point estimate of power do not adequately quantify and control the risk involved, and instead we argue for Go/No-Go decisions that utilize inference on power for better risk management and decision making.
