The MCID is the smallest change in an outcome score that patients would perceive as beneficial and that would justify a change in their care. It turns a statistically significant result into a clinically interpretable one.
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Change from baseline
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A large trial can detect a one-point improvement on a 30-point scale with a tiny p-value, even if no patient would notice the difference. The MCID provides the missing reference point: if the average improvement is well below the MCID, the result may not matter to patients, whatever its significance.
Because MCIDs depend on the population, baseline severity and method, published values vary. Use values derived in populations like yours, pre-specify the threshold in the analysis plan, and consider reporting the proportion of participants who reach it alongside mean differences. For sample size, see sample size calculation.
Minimal clinically important difference. MCII (minimal clinically important improvement) is a related term.
Anchor-based methods relate score changes to an external indicator of meaningful change; distribution-based methods use statistical properties of the scores. Anchor-based methods are generally preferred.
No. MCIDs vary by population, severity and method, so use values from comparable populations.
To define responders, choose effect sizes for sample size and interpret whether results are meaningful to patients.
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