• Omar B Mbowe, Jennifer S Gewandter, Dennis C Turk, Robert H Dworkin, and Michael P McDermott.
• Departments of Biostatistics and Computational Biology and.
• Pain. 2020 Jan 1; 161 (1): 195201195-201.

AbstractIt is often assumed that there are 2 types of pain patients: those who respond well to efficacious pain therapies and those who do not respond at all, with few people in the middle. This assumption is based on research that claims that changes in pain intensity have a bimodal distribution. The claim of bimodality has led to calls for a change in how pain clinical trials are designed and analyzed, eg, performing "responder" analyses instead of comparing group mean values to evaluate the treatment effect. We analyzed data from 4 clinical trials, 2 each of duloxetine and pregabalin, for chronic musculoskeletal and neuropathic pain conditions to critically examine the claim of bimodality of the distribution of change in pain intensity. We found that the improper construction of histograms, using unequal bin widths, was the principal flaw leading to the bimodality claim, along with the use of the oft-criticized baseline observation carried forward method for imputing missing data also serving as a contributing factor. Properly constructed histograms of absolute change in pain intensity using equal bin widths, combined with more principled methods for handling missing data, resulted in distributions that had a more unimodal appearance. Although our findings neither support nor refute the hypothesis that distinct populations of "responders" and "nonresponders" to pain interventions exist, the analyses presented in earlier work do not provide support for this hypothesis, nor for the recommendation that pain clinical trials prioritize "responder" analyses, a less efficient analysis strategy.

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