In a groundbreaking study, researchers have delved into the comparative analysis of two widely used health preference measures, EQ-5D-5L and PROMIS preference (PROPr) scores. This research, addressing a significant gap in existing literature, offers new insights into their application in healthcare, particularly in understanding patient-reported outcomes over time.
Methodology and Data Collection
The study was conducted through a health survey administered to 4,098 members of KnowledgePanel® in the United States. Among these, 1,256 respondents, all suffering from back pain, participated in a follow-up survey after six months, yielding an impressive 82% response rate. Researchers employed cross-sectional and longitudinal analyses to evaluate the correlation between EQ-5D-5L and PROPr scores. Key demographic variables and health conditions were also examined to understand their influence on these measures.
Key Findings and Market Access Implications
The study found a correlation of 0.69 between EQ-5D-5L and PROPr scores, although the intraclass correlation stood at 0.34 due to PROPr’s lower mean scores. Interestingly, both measures exhibited similar associations with demographic variables at baseline. The strong product-moment correlation (0.86) between unstandardized beta coefficients for each measure suggests that both measures have distinctive but comparable associations with various health conditions.
From a market access perspective, the ability to estimate one measure from the other using ordinary least squares (OLS) regression—with an explained variance of 48%—is particularly valuable. This capability can streamline economic evaluations and facilitate comparisons across different studies, potentially influencing reimbursement decisions and policy-making.
Insights and Inferences
Concrete and valuable inferences from the study include:
- The correlation of change from baseline to six months in both measures aligns closely with retrospective perceptions of change, highlighting their reliability in tracking patient outcomes over time.
- The beta-binomial regression model offers a slight improvement over the OLS model in predicting EQ-5D-5L scores from PROPr, indicating potential areas for methodological refinement.
- The provision of OLS regression equations is a vital tool for researchers conducting cost-effectiveness analyses and meta-analyses, promoting consistency in health economics research.
The study concludes that despite notable mean differences, EQ-5D-5L and PROPr scores show consistent associations with other variables in both cross-sectional and longitudinal contexts. These findings underscore the applicability of these measures in cost-effectiveness research, emphasizing the need for further studies to explore their validity across various conditions and interventions.
Original Article:
J Patient Rep Outcomes. 2024 Jul 19;8(1):76. doi: 10.1186/s41687-024-00749-1.
ABSTRACT
BACKGROUND: In contrast to prior research, our study presents longitudinal comparisons of the EQ-5D-5L and Patient-Reported Outcomes Measurement Information System (PROMIS) preference (PROPr) scores. This fills a gap in the literature, providing a much-needed understanding of these preference-based measures and their applications in healthcare research. Furthermore, our study provides equations to estimate one measure from the other, a tool that can significantly facilitate comparisons across studies.
METHODS: We administered a health survey to 4,098 KnowledgePanel® members living in the United States. A subset of 1,256 (82% response rate) with back pain also completed the six-month follow-up survey. We then conducted thorough cross-sectional and longitudinal analyses of the two measures, including product-moment correlations between scores, associations with demographic variables, and health conditions. To estimate one measure from the other, we used ordinary least squares (OLS) regression with the baseline data from the general population.
RESULTS: The correlation between the EQ-5D-5L and PROPr scores was 0.69, but the intraclass correlation was only 0.34 because the PROPr had lower (less positive) mean scores on the 0 (dead) to 1 (perfect health) continuum than the EQ-5D-5L. The associations between the two preference measures and demographic variables were similar at baseline. The product-moment correlation between unstandardized beta coefficients for each preference measure regressed on 22 health conditions was 0.86, reflecting similar patterns of unique associations. Correlations of change from baseline to 6 months in the two measures with retrospective perceptions of change were similar. Adjusted variance explained in OLS regressions predicting one measure from the other was 48%. On average, the predicted values were within a half-standard deviation of the observed EQ-5D-5L and PROPr scores. The beta-binomial regression model slightly improved over the OLS model in predicting the EQ-5D-5L from the PROPr but was equivalent to the OLS model in predicting the PROPr.
CONCLUSION: Despite substantial mean differences, the EQ-5D-5L and PROPr have similar cross-sectional and longitudinal associations with other variables. We provide the OLS regression equations for use in cost-effectiveness research and meta-analyses. Future studies are needed to compare these measures with different conditions and interventions to provide more information on their relative validity.
PMID:39028485 | DOI:10.1186/s41687-024-00749-1
This article has been prepared with the assistance of AI and reviewed by an editor. For more details, please refer to our Terms and Conditions. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author.
