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Naiqing Zhao

Publications and source records attributed to Naiqing Zhao.

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A Direct Approach to Simultaneous Tests of Superiority and Noninferiority with Multiple Endpoints

Simultaneous tests of superiority and non-inferiority hypotheses on multiple endpoints are often performed in clinical trials to demonstrate that a new treatment is superior over a control on at least one endpoint and non-inferior on the remaining endpoints. Existing methods tackle this problem by testing the superiority and non-inferiority hypotheses separately and control the Type I error rate each at $α$ level. In this paper we propose a unified approach to testing the superiority and non-inferiority hypotheses simultaneously. The proposed approach is based on the UI-IU test and the least favorable configurations of the combined superiority and non-inferiority hypotheses, which leads to the solution of an adjusted significance level $α'$ for marginal tests that controls the overall Type I error rate at pre-defined $α$. Simulations show that the proposed approach maintains a higher power than existing methods in the settings under investigation. Since the adjusted significance level $α'$ is obtained by controlling the Type I error rate at $α$, one can easily construct the exact $(1 - α)\%$ simultaneous confidence intervals for treatment effects on all endpoints. The proposed approach is illustrated with two real examples.

stat.ME

AAA: Triple-adaptive Bayesian designs for the identification of optimal dose combinations in dual-agent dose-finding trials

We propose a flexible design for the identification of optimal dose combinations in dual-agent dose-finding clinical trials. The design is called AAA, standing for three adaptations: adaptive model selection, adaptive dose insertion, and adaptive cohort divi- sion. The adaptations highlight the need and opportunity for innovation for dual-agent dose finding, and are supported by the numerical results presented in the proposed simulation studies. To our knowledge, this is the first design that allows for all three adaptations at the same time. We find that AAA improves the statistical inference, enhances the chance of finding the optimal dose combinations, and shortens the trial duration. A clinical trial is being planned to apply the AAA design.

stat.ME