Using multiple anchor- and distribution-based estimates to evaluate clinically meaningful change on the Functional Assessment of Cancer Therapy-Biologic Response Modifiers (FACT-BRM) instrument

Abstract

Objective: The interpretation of health-related quality of life (HRQL) data from clinical trials can be enhanced by understanding the degree of change in HRQL scores that is considered meaningful. Our objectives were to combine distribution-based and two anchor-based approaches to identify minimally important differences (MIDs) for the 27-item Trial Outcome Index (TOI), the seven-item Social Well-Being (SWB) subscale, and the six-item Emotional Well-being (EWB) subscale from the Functional Assessment of Cancer Therapy-Biological Response Modifiers (FACT-BRM) instrument.

Methods: Distribution-based MIDs were based on the standard error of measurement. Anchor-based approaches utilized patient-reported global rating of change (GRC) and change in physician-reported performance status rating (PSR). Correlations and weighted kappa statistics were used to assess association and agreement between the two anchors. FACT-BRM changes were evaluated for three time periods: baseline to month 1, month 2 to month 3, and month 5 to month 6.

Results: Association between GRC and change in PSR was poor. Correlation between the anchors and HRQL change scores was largest at month 1 and decreased through month 6. Combining results from all approaches, the MIDs identified were 5-8 points for the TOI, 2 points for the SWB subscale, and 2-3 points for the EWB subscale.

Conclusions: We combined patient-reported estimates, physician-reported estimates, and distribution-based estimates to derive MIDs for HRQL outcomes from the FACT-BRM. These results will enable interpretation of treatment group effects in a clinical trial setting, and they can be used to estimate sample size or power when designing future studies.