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Abstract:
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Patient’s treatment choice is increasingly being considered in clinical trials especially in pragmatic trials which aim to choose the best therapy for normal clinical practice. Additionally, with the creation of Patient-Centered Outcomes Research Institute (PCORI) through the Patient Protection and Affordable Care Act of 2010, more funds are being allocated to studies that center on patients. Previously published methods dealing with hybrid trials incorporating patient’s treatment choice either used ANOVA-based approach that does not allow for inclusion of covariates in the model or used likelihood methods with complex computations making it challenging for investigators to use. In our work, we propose a likelihood-based approach that can be applied to a broad class of distributions, allows for the inclusion of covariates in the model and multiple study arms, and can be executed using basic R functions. Using simulations, we evaluate these methods for a variety of continuous and categorical outcomes. Finally, we illustrate these methods by analyzing change in six-minute walking distance from a behavioral intervention study for women with heart disease.
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