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多 MS 登记处间合作研究的数据协调:以就业为例的一项研究

Data harmonization for collaborative research among MS registries: A case study in employment.

机构信息

Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA.

MS Forschungs- und Projektentwicklungs-gGmbH, German MS Register, Hannover, Germany.

出版信息

Mult Scler. 2021 Feb;27(2):281-289. doi: 10.1177/1352458520910499. Epub 2020 Mar 12.

Abstract

OBJECTIVE

To assess the feasibility of collaboration and retrospective data harmonization among three multiple sclerosis (MS) registries by investigating employment status.

METHODS

We used the Maelstrom guidelines to facilitate retrospective harmonization of data from three MS registries, including the NARCOMS (North American Research Committee on MS) Registry, German MS Register (GMSR), and United Kingdom MS (UK-MS) Register. A protocol was developed based on the guidelines, and summary-level data were used to combine results. Employment status and a limited set of factors associated with employment (age, sex, education, and disability level) were harmonized. A meta-analytic approach was used to pool estimates using a weighted average of logistic regression estimates and their variances in a random effects model.

RESULTS

Employment status, age, sex, education, and disability were mapped. The overall employment rate was 57% (11,143 employed out of 19,562 persons with MS) with the GMSR having the highest proportion of participants employed (66.2%), followed by the UK-MS (55.2%) and NARCOMS (43.0%) registries. As disability level increased, the odds of not being employed increased.

CONCLUSION

Harmonization across registries was feasible. The Maelstrom guidelines provide a valuable roadmap for conducting high-quality harmonization projects. The pooling of data sources has the potential to be an important mechanism for conducting research in MS.

摘要

目的

通过调查就业状况,评估三个多发性硬化症(MS)注册中心合作和回顾性数据协调的可行性。

方法

我们使用 Maelstrom 指南来促进三个 MS 注册中心(包括北美多发性硬化症研究委员会(NARCOMS)注册中心、德国多发性硬化症注册中心(GMSR)和英国多发性硬化症注册中心(UK-MS))的数据回顾性协调。根据指南制定了方案,并使用汇总数据来结合结果。协调了就业状况和与就业相关的一组有限因素(年龄、性别、教育程度和残疾程度)。使用加权平均逻辑回归估计值及其在随机效应模型中的方差的荟萃分析方法来汇总估计值。

结果

就业状况、年龄、性别、教育程度和残疾程度得到了映射。总体就业率为 57%(19562 名 MS 患者中有 11143 人就业),其中 GMSR 的就业比例最高(66.2%),其次是 UK-MS(55.2%)和 NARCOMS(43.0%)注册中心。随着残疾程度的增加,未就业的可能性增加。

结论

各注册中心之间的协调是可行的。Maelstrom 指南为进行高质量的协调项目提供了有价值的路线图。数据源的汇总有可能成为 MS 研究的重要机制。

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