Statistics and ethics: models for strengthening protection of human subjects in clinical research.

I n this issue of PNAS, Press (1) proposes a method that could substantially advance ethical approaches to clinical trials and comparative effectiveness research. Such advances are needed to harvest the potential benefit of electronic medical information, allowing far greater numbers and far greater specificity of comparisons among diagnostic or treatment modalities in demographic, phenotypic, and genetically distinct comparative populations. Press (1) deals with the optimization of patient selection for clinical trials that have large or infinite patient horizons. The objective is to assign patients to one of two treatment groups (‘‘arms’’) with total cost of treatment being kept to a minimum. ‘‘Cost’’ is not just simple dollar cost, but instead, a combination of measures of loss associated with assignment to the inferior treatment. To make the method relevant to comparative effectiveness research, dollar cost is tallied only when the inferior treatment led to a failed patient outcome. The method is the ‘‘two-armed bandit problem’’ of decision analysis, using a Bayesian approach to estimating success rates (2, 3).