Combining Distribution- and Anchor-Based Approaches to Determine Minimally Important Differences

Abstract

Health-related quality of life (HRQOL) is an important endpoint in cancer clinical trials and in cancer treatment in general; however, the meaningfulness of HRQOL scores may not be apparent to clinicians or researchers. Minimally important differences (MIDs) can enhance the interpretability of HRQOL scores by identifying differences likely to be meaningful to patients and clinicians. This article's objective is to describe and provide examples of approaches we have used to identify MIDs for instruments in the Functional Assessment of Chronic Illness Therapy (FACIT) measurement system. Distribution- and anchor-based approaches are described and illustrated. We also discuss the importance of assessing the appropriateness of anchors, and we provide suggestions for combining results into a single range of plausible MIDs. MIDs for FACIT instruments established to date are summarized, and general guidelines that can be used to estimate MIDs for other FACIT instruments are provided. Applications of MIDs in research are illustrated.

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