Fay Michael P, Follmann Dean A
Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Rockville, MD, USA
Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Rockville, MD, USA.
Clin Trials. 2016 Dec;13(6):632-640. doi: 10.1177/1740774516654861. Epub 2016 Jul 17.
BACKGROUND/AIMS: In testing for non-inferiority of anti-infective drugs, the primary endpoint is often the difference in the proportion of failures between the test and control group at a landmark time. The landmark time is chosen to approximately correspond to the qth historic quantile of the control group, and the non-inferiority margin is selected to be reasonable for the target level q. For designing these studies, a troubling issue is that the landmark time must be pre-specified, but there is no guarantee that the proportion of control failures at the landmark time will be close to the target level q. If the landmark time is far from the target control quantile, then the pre-specified non-inferiority margin may not longer be reasonable. Exact variable margin tests have been developed by Röhmel and Kieser to address this problem, but these tests can have poor power if the observed control failure rate at the landmark time is far from its historic value.
We develop a new variable margin non-inferiority test where we continue sampling until a pre-specified proportion of failures, q, have occurred in the control group, where q is the target quantile level. The test does not require any assumptions on the failure time distributions, and hence, no knowledge of the true [Formula: see text] control quantile for the study is needed.
Our new test is exact and has power comparable to (or greater than) its competitors when the true control quantile from the study equals (or differs moderately from) its historic value. Our nivm R package performs the test and gives confidence intervals on the difference in failure rates at the true target control quantile. The tests can be applied to time to cure or other numeric variables as well.
A substantial proportion of new anti-infective drugs being developed use non-inferiority tests in their development, and typically, a pre-specified landmark time and its associated difference margin are set at the design stage to match a specific target control quantile. If through changing standard of care or selection of a different population the target quantile for the control group changes from its historic value, then the appropriateness of the pre-specified margin at the landmark time may be questionable. Our proposed test avoids this problem by sampling until a pre-specified proportion of the controls have failed.
背景/目的：在抗感染药物非劣效性试验中，主要终点通常是在一个标志性时间点试验组与对照组失败比例的差异。标志性时间的选择大致对应于对照组的第q个历史分位数，并且非劣效性界值的选择对于目标水平q而言是合理的。在设计这些研究时，一个棘手的问题是标志性时间必须预先设定，但无法保证在标志性时间点对照组的失败比例会接近目标水平q。如果标志性时间远离目标对照分位数，那么预先设定的非劣效性界值可能就不再合理。Röhmel和Kieser已经开发了精确可变界值检验来解决这个问题，但是如果在标志性时间点观察到的对照组失败率与其历史值相差甚远，这些检验的效能可能较差。
我们开发了一种新的可变界值非劣效性检验，即持续抽样直到对照组出现预先设定的失败比例q，其中q是目标分位数水平。该检验不需要对失败时间分布做任何假设，因此，无需了解该研究中真实的对照组分位数。
我们的新检验是精确的，并且当研究中的真实对照分位数等于（或与）其历史值（适度）不同时，其效能与其竞争对手相当（或更高）。我们的nivm R包可执行该检验，并给出真实目标对照分位数处失败率差异的置信区间。这些检验也可应用于治愈时间或其他数值变量。
正在研发的大量新型抗感染药物在其研发过程中使用非劣效性检验，并且通常在设计阶段设定一个预先指定的标志性时间及其相关的差异界值，以匹配特定的目标对照分位数。如果通过改变护理标准或选择不同的人群，对照组的目标分位数与其历史值不同，那么在标志性时间点预先设定的界值的合理性可能存在疑问。我们提出的检验通过持续抽样直到预先设定比例的对照组失败来避免这个问题。
