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Abstract:
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There is a need for statistical methods appropriate for the analysis of clinical trials from a personalized-medicine viewpoint as opposed to the common statistical practice that simply examines averages. We present an approach to quantifying, reporting and analyzing individual benefits of medical or behavioral treatments to severely ill patients with chronic conditions, using clinical trials data. The approach is based on a framework for measuring the severity of a chronic disease and the benefits treatments provide to individuals, which utilizes regression models with random coefficients. We present a very flexible family of probability distributions of individual benefits that depend on treatment duration and covariates. The prediction of future benefits in new patients is also examined. We illustrate with a clinical trial comparing ophthalmological treatments for diabetic macular edema.
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