PDF(Pubmed)
Abstract：
Necessity for finding improved intervention in many legacy therapeutic areas are of high priority. This has the potential to decrease the expense of medical care and poor outcomes for many patients. Typically, clinical efficacy is the primary evaluating criteria to measure any beneficial effect of a treatment. Albeit, there could be situations when several other factors (e.g. side-effects, cost-burden, less debilitating, less intensive, etc.) which can permit some slightly less efficacious treatment options favorable to a subgroup of patients. This often leads to non-inferiority (NI) testing. NI trials may or may not include a placebo arm due to ethical reasons. However, when included, the resulting three-arm trial is more prudent since it requires less stringent assumptions compared to a two-arm placebo-free trial. In this article, we consider both Frequentist and Bayesian procedures for testing NI in the three-arm trial with binary outcomes when the functional of interest is risk difference. An improved Frequentist approach is proposed first, which is then followed by a Bayesian counterpart. Bayesian methods have a natural advantage in many active-control trials, including NI trial, as it can seamlessly integrate substantial prior information. In addition, we discuss sample size calculation and draw an interesting connection between the two paradigms.
摘要：
在许多传统治疗领域中找到改善的干预措施的必要性是高度优先的。这有可能降低许多患者的医疗费用和不良结果。通常,临床疗效是衡量治疗任何有益效果的主要评价标准.尽管,可能存在其他几个因素(例如副作用，成本负担，不那么虚弱，不太密集，等。)，这可以允许一些对患者亚组有利的稍微不太有效的治疗选择。这通常导致非劣效性(NI)测试。由于伦理原因，NI试验可能包括也可能不包括安慰剂组。然而,当包括时，与不含安慰剂的双臂试验相比,由此产生的三臂试验更谨慎,因为其需要的假设不那么严格.在这篇文章中,当感兴趣的功能是风险差异时,我们考虑Frequentist和Bayesian两种方法在具有二元结局的三组试验中检测NI.首先提出了一种改进的Frequentist方法，然后是贝叶斯对应物。贝叶斯方法在许多主动控制试验中具有天然的优势，包括NI试验,因为它可以无缝地集成大量的先验信息。此外,我们讨论了样本量计算，并在两个范式之间得出了有趣的联系。
