The design of a clinical trial is often complicated by the multi-systemic nature of the disease; a single endpoint often cannot capture the spectrum of potential therapeutic benefits. Multi-domain outcomes which take into account patient heterogeneity of disease presentation through measurements of multiple symptom/functional domains are an attractive alternative to a single endpoint. A multi-domain test with adaptive weights is proposed to synthesize the evidence of treatment efficacy over numerous disease domains. The test is a weighted sum of domain-specific test statistics with weights selected adaptively via a data-driven algorithm. The null distribution of the test statistic is constructed empirically through resampling and does not require estimation of the covariance structure of domain-specific test statistics. Simulations show that the proposed test controls the type I error rate, and has increased power over other methods such as the O'Brien and Wei-Lachin tests in scenarios reflective of clinical trial settings. Data from a clinical trial in a rare lysosomal storage disorder were used to illustrate the properties of the proposed test. As a strategy of combining marginal test statistics, the proposed test is flexible and readily applicable to a variety of clinical trial scenarios.
Keywords: adaptive weight; multiple testing; nonparametric multivariate test; rare disease; treatment effect.
© 2019 John Wiley & Sons Ltd.