Minimally Clinically Important Differences

Anchor-based MCID estimation and its sample-size implications for neurodegenerative disease trials

2026-06-07 18:16 PDT

Overview

A statistically significant treatment effect is not automatically clinically meaningful. The minimally clinically important difference (MCID) – the smallest change in a patient-reported or clinician-rated outcome that a patient would recognize as important – provides the bridge between statistical inference and clinical relevance, and directly determines the sample sizes required for definitive trials.

This program develops anchor-based MCID estimates for rating scales used as primary endpoints in Alzheimer’s disease and related neurodegenerative conditions, derives the implied sample-size requirements, and examines the sensitivity of those requirements to MCID definition and covariance structure.

Papers in development

  • Anchor-based MCID estimation for the Clinical Dementia Rating Sum of Boxes (CDR-SB) and its sample-size implications for confirmatory Alzheimer’s disease trials.

  • Empirical variance-covariance matrices from completed ADCS trials as simulation inputs for sample-size analysis.

Methods

Anchor-based MCID estimation (distribution-based, anchor-based with global ratings of change); CDR trajectory modeling from multi-cohort registry data; power and sample-size curves via pwr and custom simulation; zzlongplot for CDR visualization; APA-format citation and reproducible Rmd rendering.

Selected publication

Golbe, L. I., & Thomas, R. G. (2026). Minimally clinically important differences for PSPRS subscales in progressive supranuclear palsy. Alzheimer’s & Dementia: Translational Research & Clinical Interventions. [Published]

Publications

Additional work on MCID methodology and related sample-size methods is available through the full publications list by filtering on sample-size or alzheimers-disease.