As the implementation of Patient-Reported Outcomes Measurement Information System (PROMIS) scales has increased, so has the number of studies linking legacy scale scores to PROMIS scale scores. Variability in linked scores for a given PROMIS score can be considerable, leading to potential bias. An alternative method is imputation using a bridge study. We sought to compare linking to this alternative novel method in group-level analyses using linked legacy scores. Adult patients who completed PROMIS Depression and Patient Health Questionnaire (PHQ-9) were included. We randomly allocated data samples to be missing either PROMIS Depression or PHQ-9. We estimated PROMIS T scores using six methods: Linking methods by Choi et al. (2014), linking in our internal data, imputation using bridge study data from external data and from our internal data, each with and without patient demographics. Estimated mean PROMIS T scores using the linking and imputation methods were compared to actual PROMIS T scores across varying proportions of missingness and sample size. We also compared regression coefficients for the six estimation methods to a model using actual PROMIS T scores. Mean estimated versus actual PROMIS T scores varied between 1 and 4 points for the linking methods and within 0.4 points for the imputation method using internal data with patient demographics. The imputation methods had estimated regression coefficients closer to that of the model using actual scores as compared to the linking methods. For group-level analyses, imputation using a bridge study may be a feasible alternative to using linked scores or can be used as a sensitivity analysis. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

中文翻译：

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涉及从遗留量表链接到 PROMIS 量表的分数的组级分析：使用插补的新替代方法。

随着患者报告结果测量信息系统 (PROMIS) 量表的实施增加，将旧量表分数与 PROMIS 量表分数联系起来的研究数量也在增加。给定 PROMIS 分数的关联分数的可变性可能相当大，从而导致潜在的偏差。另一种方法是使用桥梁研究进行插补。我们试图在使用链接的遗留分数的组级分析中比较与这种替代新方法的链接。包括完成 PROMIS 抑郁症和患者健康问卷 (PHQ-9) 的成年患者。我们将数据样本随机分配为缺失 PROMIS 抑郁或 PHQ-9。我们使用六种方法估计了 PROMIS T 分数： Choi 等人的链接方法。(2014)，链接我们的内部数据，使用来自外部数据和我们内部数据的桥梁研究数据进行插补，每个有和没有患者人口统计数据。将使用链接和插补方法的估计平均 PROMIS T 分数与不同比例的缺失和样本大小的实际 PROMIS T 分数进行比较。我们还将六种估计方法的回归系数与使用实际 PROMIS T 分数的模型进行了比较。对于链接方法，平均估计值与实际 PROMIS T 得分在 1 到 4 分之间变化，对于使用具有患者人口统计的内部数据的插补方法，在 0.4 分以内。与链接方法相比，插补方法估计的回归系数更接近使用实际分数的模型的回归系数。对于组级分析，使用桥接研究的插补可能是使用关联分数的可行替代方案，也可以用作敏感性分析。（PsycInfo 数据库记录 (c) 2021 APA，