Giving Meaning to Differences in BREAST-Q Scores Academic Article uri icon

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abstract

  • BACKGROUND: The reconstruction module of the BREAST-Q patient-reported outcome measure is frequently used by investigators and in clinical practice. A minimal important difference establishes the smallest change in outcome measure score that patients perceive to be important. To enhance interpretability of the BREAST-Q reconstruction module, the authors determined minimal important difference estimates using distribution-based methods. METHODS: An analysis of prospectively collected data from 3052 Mastectomy Reconstruction Outcomes Consortium patients was performed. The authors used distribution-based methods to investigate the minimal important difference for the entire patient sample and three clinically relevant groups. The authors used both 0.2 SD units (effect size) and the standardized response mean value of 0.2 as distribution-based criteria. Clinical experience was used to guide and assess appropriateness of results. RESULTS: A total of 3052 patients had BREAST-Q data available for analysis. The average age and body mass index were 49.5 and 26.8, respectively. The minimal important difference estimates for each domain were 4 (Satisfaction with Breasts), 4 (Psychosocial Well-being), 3 (Physical Well-being), and 4 (Sexual Well-being). The minimal important difference estimates for each domain were similar when compared within the three clinically relevant groups. CONCLUSIONS: The authors propose that a minimal important difference score of 4 points on the transformed 0 to 100 scale is clinically useful when assessing an individual patient's outcome using the reconstruction module of the BREAST-Q. When designing research studies, investigators should use the minimal important difference estimate for their domain of interest when calculating sample size. The authors acknowledge that distribution-based minimal important differences are estimates and may vary based on patient population and context.

publication date

  • January 2020