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Abstract:
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The individual way of responding to treatment is designated as the treatment response. The major concepts of the treatment response approach are the aggregation, treatment-outcome complex, sensitivity to treatment, and capacity for spontaneous recovery. Contrary to the treatment effect (defined in RCT as risk reduction), the treatment response approach derives from the assumptions of the uniqueness of each member of the population, relatedness of the co-occurring events, and possibility of making valid causal inferences from single cases. The data driven deterministic hypotheses of non-random aggregation of the elements, events, and characteristics are subject to contrasting with the hypotheses of their random gathering. The approach can provide a framework for deep learning. Complementing the treatment effect approach with analysis of the treatment response can have substantial implications in the areas of: 1) identification and prediction of the individual effect of treatment; 2) identification and prediction of spontaneous recovery and sensitivity to the treatment, and 3) generalizing the results of RCT and predicting the individual results of treatment in the general population
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