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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. A patient is severely ill if the patient’s basal severity is close to one. We present a very flexible family of probability distributions of individual benefits that depend on treatment duration and covariates. Our approach may enrich the statistical analysis of clinical trials of severely ill patients because it allows investigating the probability distribution of individual benefits in the patient population and the variables that influence it. We can also measure benefits achieved in new patients. We illustrate our approach using data from a clinical trial of the anti-depressant imipramine.
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