Division of General Internal Medicine and Health Services Research, UCLA Department of Medicine, 1100 Glendon Avenue Suite 850, Los Angeles, CA, USA.
Patient Reported Outcomes, Value and Experience (PROVE) Center, Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA.
J Patient Rep Outcomes. 2024 Jul 19;8(1):76. doi: 10.1186/s41687-024-00749-1.
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.
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.
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.
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.
与先前的研究相比,我们的研究对 EQ-5D-5L 和患者报告的结果测量信息系统(PROMIS)偏好(PROPr)评分进行了纵向比较。这填补了文献中的空白,为这些基于偏好的衡量标准及其在医疗保健研究中的应用提供了急需的理解。此外,我们的研究提供了从一种衡量标准估计另一种衡量标准的方程,这是一个可以极大促进研究之间比较的工具。
我们向居住在美国的 4098 名 KnowledgePanel 成员进行了健康调查。其中有 1256 名(82%的回复率)有背痛的参与者还完成了六个月的随访调查。然后,我们对这两种衡量标准进行了全面的横断面和纵向分析,包括评分之间的积差相关、与人口统计学变量和健康状况的关联。为了从一种衡量标准估计另一种衡量标准,我们使用普通最小二乘法(OLS)回归,使用一般人群的基线数据。
EQ-5D-5L 和 PROPr 评分之间的相关系数为 0.69,但组内相关系数仅为 0.34,因为 PROPr 在 0(死亡)到 1(完美健康)连续体上的平均得分较低(不太积极)。在基线时,两种偏好衡量标准与人口统计学变量的关联相似。将每个偏好衡量标准回归到 22 种健康状况的未标准化贝塔系数之间的积差相关系数为 0.86,反映出相似的独特关联模式。两种衡量标准在从基线到 6 个月的变化与对变化的回顾性感知之间的相关性相似。在从另一种衡量标准预测一种衡量标准的 OLS 回归中,调整后的方差解释率为 48%。平均而言,预测值与观察到的 EQ-5D-5L 和 PROPr 评分相差半标准差。贝塔二项式回归模型在从 PROPr 预测 EQ-5D-5L 方面略优于 OLS 模型,但在从 PROPr 预测 PROPr 方面与 OLS 模型相当。
尽管平均差异很大,但 EQ-5D-5L 和 PROPr 与其他变量具有相似的横断面和纵向关联。我们提供了 OLS 回归方程,用于成本效益研究和荟萃分析。需要进一步的研究来比较这些衡量标准在不同情况下和干预措施中的表现,以提供更多关于它们相对有效性的信息。