Placebo Response as a Latent Characteristic: Application to Analysis of Sequential Parallel Comparison Design Studies

• 成果类型: Article
• 署名作者: Rybin, Denis; Lew, Robert; Pencina, Michael J.; Fava, Maurizio; Doros, Gheorghe
• 署名单位: Boston University; Harvard University; Harvard University Medical Affiliates; Massachusetts General Hospital; Harvard Medical School
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2017.1375930
• 发表日期: 2018
• 页码: 1411-1430
• 关键词: clinical-trials; maximum-likelihood; enrichment; disorders; time

摘要

In clinical trials, placebo response can affect the inference about efficacy of the studied treatment. It is important to have a robust way to classify trial subjects with respect to their response to placebo. Simple, criterion-based classification may lead to classification error and bias the inference. The uncertainty about placebo response characteristic has to be factored into the treatment effect estimation. We propose a novel approach that views the placebo response as a latent characteristic and the study sample as an unlabeled mixture of placebo responders and placebo nonresponders. The likelihood-based methodology is used to estimate the treatment effect corrected for placebo response as defined within sequential parallel comparison design.