多站点健康研究整合互补数据源：对垂直划分数据统计推断方法的综述
Multi-Site Health Research Integrating Complementary Data Sources: A Scoping Review of Statistical Inference Methods for Vertically Partitioned Data
AI总结：
本文综述了垂直划分数据的统计推断方法，发现线性与逻辑回归框架应用最广，但多数方法缺乏与汇总分析等效性验证，且通信效率低，隐私保护不足。
摘要：
为应对健康问题的多维性质，健康研究的进步往往需要整合不同数据源的信息。当互补信息分布在不同机构时，垂直方法可实现分析结果而无需共享或汇总个体数据。本研究旨在识别现有垂直方法并描述其方法学特性及在健康数据中的使用情况。通过四个跨学科数据库进行综述，系统提取了垂直方法的可比性、通信方案效率和保密性。此外，筛选引用包含文章的研究以识别实际应用。2887篇初始筛选文章中，30篇被纳入综述。线性与逻辑回归框架的推断任务最频繁。等效于汇总分析未被系统探讨，多数方法需多次通信。几乎所有文章描述其方法为隐私保护，但少数提供了隐私评估。现有方法在统计推断方面的范围仍较有限，多数方法无法同时实现与集中分析等效、高通信效率和个体数据保护。
英文摘要：
To address the multidimensional nature of health-related questions, advances in health research often require integrating information from various data sources within statistical analyses. When complementary information pertaining to the same set of individuals are distributed across different institutions, vertical methods make it possible to obtain analysis results without sharing or pooling individual-level data. To guide stakeholders toward a transparent use of vertical methods, this study aims to (1) Identify existing vertical methods enabling statistical inference; and (2) Characterize the methodological properties of these methods and the current extent of their use with health data. We conducted a scoping review using four interdisciplinary databases. We then systematically extracted the characteristics of identified vertical methods with respect to comparability with the pooled analysis, efficiency of communication schemes and confidentiality. We additionally screened studies that cited included articles to identify applications on vertically partitioned real-world health data. Among 2887 articles initially screened, 30 were included in the review. Inference for the linear and the logistic regression framework were the most frequent statistical inference tasks undertaken in proposed methods. Equivalence with the pooled analyses was not systematically addressed and most methods required multiple communications between participating parties. Almost all articles described their approach as privacy-preserving, although a minority provided privacy assessments. The scope of existing approaches enabling statistical inference for vertically partitioned data is still relatively limited. Most existing methods do not concurrently achieve results equivalent to centralized analyses, high communication efficiency, and guaranteed protection of individual-level data.
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