Tang Xiaodan, Hays Ron D, Cella David, Acaster Sarah, Schalet Benjamin David, Sikora Kessler Asia, Vera Llonch Montserrat, Hanmer Janel
Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Department of Medicine, Division of General Internal Medicine & Health Services Research, University of California, Los Angeles, CA, USA.
Med Decis Making. 2025 Aug;45(6):740-752. doi: 10.1177/0272989X251340990. Epub 2025 Jun 13.
ObjectivesThe EQ-5D-5L and Patient-Reported Outcomes Measurement Information System (PROMIS®) preference score (PROPr) are preference-based measures. This study compares mapping and linking approaches to align the PROPr and the PROMIS domains included in PROPr plus Anxiety with EQ-5D-5L item responses and preference scores.MethodsA general population sample of 983 adults completed the online survey. Regression-based mapping methods and item response theory (IRT) linking methods were used to align scores. Mapping was used to predict EQ-5D-5L item responses or preference scores using PROMIS domain scores. Equating strategies were applied to address regression to the mean. The linking approach estimated item parameters of EQ-5D-5L based on the PROMIS score metric and generated bidirectional crosswalks between EQ-5D-5L item responses and relevant PROMIS domain scores.ResultsEQ-5D-5L item responses were significantly accounted for by PROMIS domains of Anxiety, Depression, Fatigue, Pain Interference, Physical Function, Social Roles, and Sleep Disturbance. EQ-5D-5L preference scores were accounted for by the same PROMIS domains, excluding Anxiety and Fatigue, and by the PROPr preference scores. IRT-linking crosswalks were generated between EQ-5D-5L item responses and PROMIS domains of Physical Function, Pain, and Depression. Small differences were found between observed and predicted scores for all 3 methods. The direct mapping approach (directly predicting EQ-5D-5L scores) with the equipercentile equating strategy proved superior to the linking method due to improved prediction accuracy and comparable score range coverage.ConclusionsThe PROPr and the PROMIS domains included in the PROMIS-29+2 predict EQ-5D-5L preference scores or item responses. Both methods can generate acceptably precise EQ-5D-5L preference scores, with the direct mapping approach using the equating strategy offering better precision. We summarized recommended score conversion tables based on available and desired scores.HighlightsThis study compares mapping (score prediction) and IRT-based linking approaches to align the PROPr and the PROMIS domains with EQ-5D-5L item responses and preference scores.Researchers, clinicians, and stakeholders can use this study's regression formulas and score crosswalks to convert scores between PROMIS and EQ-5D-5L.Mapping can generate more precise scores, while linking offers greater flexibility in score estimation when fewer PROMIS domain scores are collected.
目标
EQ-5D-5L和患者报告结局测量信息系统(PROMIS®)偏好得分(PROPr)是基于偏好的测量指标。本研究比较了映射和链接方法,以使PROPr以及PROPr加焦虑症中包含的PROMIS领域与EQ-5D-5L项目反应和偏好得分相一致。
方法
983名成年人的一般人群样本完成了在线调查。基于回归的映射方法和项目反应理论(IRT)链接方法用于使得分一致。映射用于使用PROMIS领域得分预测EQ-5D-5L项目反应或偏好得分。应用等值策略来解决均值回归问题。链接方法基于PROMIS得分度量估计EQ-5D-5L的项目参数,并在EQ-5D-5L项目反应和相关PROMIS领域得分之间生成双向交叉表。
结果
EQ-5D-5L项目反应在很大程度上可由焦虑、抑郁、疲劳、疼痛干扰、身体功能、社会角色和睡眠障碍等PROMIS领域解释。EQ-5D-5L偏好得分可由相同的PROMIS领域(不包括焦虑和疲劳)以及PROPr偏好得分解释。在EQ-5D-5L项目反应与身体功能、疼痛和抑郁等PROMIS领域之间生成了IRT链接交叉表。在所有3种方法中,观察得分与预测得分之间存在微小差异。由于预测准确性提高且得分范围覆盖相当,采用等百分位等值策略的直接映射方法(直接预测EQ-5D-5L得分)被证明优于链接方法。
结论
PROMIS-29+2中包含的PROPr和PROMIS领域可预测EQ-5D-5L偏好得分或项目反应。两种方法都能生成精度可接受的EQ-5D-5L偏好得分,采用等值策略的直接映射方法精度更高。我们根据可用得分和期望得分总结了推荐的得分转换表。
要点
本研究比较了映射(得分预测)和基于IRT的链接方法,以使PROPr和PROMIS领域与EQ-5D-5L项目反应和偏好得分相一致。
研究人员、临床医生和利益相关者可使用本研究的回归公式和得分交叉表在PROMIS和EQ-5D-5L之间转换得分。
映射可生成更精确的得分,而当收集的PROMIS领域得分较少时,链接在得分估计方面提供更大的灵活性。