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Abstract

Methods, software, and systems for evaluating the response of a patient afflicted with a disease to a therapeutic regimen for the disease are described. In one aspect, the present methods, systems, and software are provided for evaluating the utility of a treatment regimen for treating a patient afflicted with a disease. In one embodiment of this aspect, the value of at least one diagnostic variable relating to a statistical model describing the utility of the treatment regimen is determined. The statistical model is derived using a robustified similarity metric least squares (SMILES) analysis of the response to the treatment regimen which has been adapted to include discriminant and logistical analysis. The value of the diagnostic variable is then applied to the model to provide an estimated utility of the treatment regimen in treating the patient. Using the methods, software, and apparatus described herein, robust, statistically significant models of patient responsiveness that reduce the problems associated with present treatment response prediction methods that are brittle and oversimplify the complex interactions among treatment variables can assist patients and clinicians in determining therapies.

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First Claim