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A new preference-based analysis for randomized trials can estimate treatment acceptability and effect in compliant patients.

机译:一种新的基于偏好的随机试验分析可以评估依从性患者的治疗可接受性和效果。

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摘要

BACKGROUND AND OBJECTIVES: Development of a new method of analysis to evaluate the acceptability of (or preferences for) the treatments in a randomized trial, and the benefit of treatment among compliers. MATERIALS AND METHODS: We characterize trial participants through the groups who would: accept either treatment if offered (compliers); refuse one treatment but accept the other if it is offered to them (two groups of preferers); or prefer one treatment and insist on it if it is not offered to them initially (two groups of insisters). RESULTS: We show that in our framework, one can always estimate the proportions of patients in these five preference groups. However, constraints are required to estimate the corresponding outcome rates, and thus estimate the treatment effect in the compliers. We propose two possible sets of constraints and illustrate them by numerical examples. CONCLUSIONS: The traditional intention-to-treat analysis avoids biases associated with the alternative per-protocol or as-treated approaches, but it provides imperfect information about the expected treatment effect among patients who are committed to taking the treatment. Many physicians and patients want to know the expected benefit if they adhere to the therapy. Our preference-based analysis provides an estimate of treatment benefit among such patients.
机译:背景与目的:开发一种新的分析方法以评估随机试验中治疗的可接受性(或偏爱),以及合规者的治疗获益。材料和方法:我们通过以下人群来描述试验参与者的特征:拒绝接受一种治疗,但接受另一种治疗(两组优待者);或者更喜欢一种治疗,如果最初没有提供给他们,则坚持使用(两组坚持者)。结果:我们表明,在我们的框架中,人们始终可以估算出这五个偏好组中患者的比例。但是,需要约束来估计相应的结果率,从而估计编译器中的治疗效果。我们提出了两组可能的约束条件,并通过数值示例进行了说明。结论:传统的意向治疗分析避免了与替代方案或按治疗方案相关的偏见,但它在致力于接受治疗的患者中提供了关于预期治疗效果的不完善信息。许多医生和患者希望了解他们坚持治疗的预期益处。我们基于偏好的分析提供了此类患者的治疗获益估计。

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