Drop the “M”: Minimally Important Difference and Change Are Not Independent Properties of an Instrument and Cannot Be Determined as a Single Value Using Statistical Methods

Objectives Patient-reported outcome (PRO) instruments typically give a score on a scale, making it difficult to know whether a given difference between an experimental treatment and control in a clinical trial is large enough to warrant use of that treatment. The minimally important difference (MID) is used for designing and interpreting clinical research. We aim to explore the rationale and statistical underpinnings of the idea that MID can be defined as an inherent property of a particular PRO instrument. Methods We undertook a narrative review of the empirical and methodologic literature on MIDs. Results Both methods of estimating MID—anchor or distribution based—are, at best, highly questionable. Anchor-based methods are problematic because patients may experience changes in health that are poorly captured by a general anchor question about whether health is better, worse, or about the same; distribution-based methods are conditioned on sample-dependent variability of an instrument, and there is no clear rationale as to why the relevance of a specific patient’s change in health can be meaningfully referenced to some prior sample’s score dispersion. Moreover, the degree of change we would require on a given scale is higher for a treatment that is costly, invasive, unpleasant, or associated with side effects than it is for a safe, well-tolerated, cheap, and convenient alternative or one that is associated with other benefits. Conclusions MID must be estimated within a specific study context. It is best to think of PRO measures in terms of “ID” and leave the “M” to case-by-case, context-based interpretation.