Collaborative causal inference with a distributed data-sharing management

TL;DR

This paper introduces a privacy-preserving distributed causal inference framework for multicenter clinical trials, enabling analysis without raw data sharing, thus overcoming data sharing barriers and maintaining statistical power.

Contribution

The paper proposes a novel distributed causal inference method that uses only summary statistics, avoiding raw data sharing and addressing data privacy and heterogeneity issues.

Findings

The method maintains statistical power close to centralized analysis.

It offers strong data privacy protections.

It performs well in simulations and real clinical trial data.

Abstract

Data sharing barriers are paramount challenges arising from multicenter clinical trials where multiple data sources are stored in a distributed fashion at different local study sites. Merging such data sources into a common data storage for a centralized statistical analysis requires a data use agreement, which is often time-consuming. Data merging may become more burdensome when causal inference is of primary interest because propensity score modeling involves combining many confounding variables, and systematic incorporation of this additional modeling in meta-analysis has not been thoroughly investigated in the literature. We propose a new causal inference framework that avoids the merging of subject-level raw data from multiple sites but needs only the sharing of summary statistics. The proposed collaborative inference enjoys maximal protection of data privacy and minimal sensitivity to unbalanced data distributions across data sources. We show theoretically and numerically that the new distributed causal inference approach has little loss of statistical power compared to the centralized method that requires merging the entire data. We present large-sample properties and algorithms for the proposed method. We illustrate its performance by simulation experiments and a real-world data example on a multicenter clinical trial of basal insulin treatment for reducing the risk of post-transplantation diabetes among kidney-transplant patients.