Comparison of an ordinal endpoint to time-to-event, longitudinal, and binary endpoints for use in evaluating treatments for severe influenza requiring hospitalization
Comparison of an ordinal endpoint to time-to-event, longitudinal, and binary endpoints for use in evaluating treatments for severe influenza requiring hospitalization
复制标题
DOI：
10.1016/j.conctc.2019.100401
复制
发表时间：
2019-09-01
影响因子：
1.5
通讯作者：
Neaton, James D.
中科院分区：
文献类型：
--
作者：
Peterson, Ross L.;Vock, David M.;Neaton, James D.
背景/目标：美国食品和药物管理局建议研究开发明确和可靠的终点，以评估需要住院治疗的严重流感的治疗方法。一项静脉注射免疫球蛋白（WIG）治疗重度流感（FLU-IVIG）的随机安慰剂对照试验中使用了一种新型6类顺序终点，即7天后患者健康状况，范围从死亡到出院并恢复正常活动。我们比较的权力的顺序端点的比例优势模型下的其他类型的端点作为一个功能的各种试验parameters.Methods：我们使用了封闭形式的分析和实证模拟比较的权力的顺序端点的时间到事件的纵向，和二进制端点。在模拟环境中，我们改变了治疗效果和安慰剂组在整个随访期间的分布，并考虑了基线健康状况的调整。在分析设置中，高粒度的有序端点提供了比时间更大的功效，安慰剂组中大多数患者在第7天自然进展至出院类别或远离出院类别时的事件终点第7天出院。在模拟环境中，调整基线健康状况普遍提高比例优势模型的功效。在不同的安慰剂组中，顺序终点的分布不考虑基线健康状态的调整，对于某些治疗效果，只有至事件发生时间终点的把握度高于顺序终点。在该病例研究中，对于治疗效果和安慰剂组分布的大多数情况，FLU-IVIG顺序终点提供了比至事件发生时间、二元和纵向终点更大的把握度，包括FLU-WIG研究的目标人群。仅当安慰剂组中的许多患者在第7天处于出院尖端时，至事件发生时间终点才超过顺序终点，并且延长至事件发生时间终点的随访期以允许发生其他事件。我们评估流感试验几个潜在终点功效的一般方法可用于设计具有不同目标人群的其他流感试验和其他疾病领域的其他试验。
Background/aims: The Food and Drug Administration recommends research into developing well-defined and reliable endpoints to evaluate treatments for severe influenza requiring hospitalization. A novel 6-category ordinal endpoint of patient health status after 7 days that ranges from death to hospital discharge with resumption of normal activities is being used in a randomized placebo-controlled trial of intravenous immunoglobulin (WIG) for severe influenza (FLU-IVIG). We compare the power of the ordinal endpoint under a proportional odds model to other types of endpoints as a function of various trial parameters.Methods: We used closed-form analysis and empirical simulation to compare the power of the ordinal endpoint to time-to-event longitudinal, and binary endpoints. In the simulation setting, we varied the treatment effect and the distribution of the placebo group across the follow-up period with consideration of adjustment for baseline health status.Results: In the analytic setting, ordinal endpoints of high granularity provided greater power than time-to-event endpoints when most patients in the placebo group had either naturally progressed to the category of hospital discharge by day 7 or were far from hospital discharge on day 7. In the simulation setting, adjustment for baseline health status universally raised power for the proportional odds model. Across different placebo group distributions of the ordinal endpoint regardless of adjustment for baseline health status, only time-to-event endpoints yielded higher power than the ordinal endpoint for certain treatment effects.Conclusions: In this case study, the FLU-IVIG ordinal endpoint provided greater power than time-to-event, binary, and longitudinal endpoints for most scenarios of the treatment effect and placebo group distribution, including the target population studied for FLU-WIG. The ordinal endpoint was only surpassed by the time-toevent endpoint when many patients in the placebo group were on the cusp of hospital discharge on day 7 and the follow-up period for the time-to-event endpoint was extended to allow for additional events. Our general approach for evaluating the power of several potential endpoints for an influenza trial can be used for designing other influenza trials with different target populations and for other trials in other disease areas.