Distributed Regression Analysis Application in Large Distributed Data Networks: Analysis of Precision and Operational Performance
| Autor: | Qoua L. Her, Denise M. Boudreau, Yury Vilk, David Tabano, Zilu Zhang, Jack Hamilton, Sengwee Toh, Jessica G. Young, Marsha A. Raebel, Ron L. Johnson, Jessica Malenfant |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Operational performance
pharmacoepidemiology Computer science Computer applications to medicine. Medical informatics R858-859.7 Health Informatics computer.software_genre PopMedNet Execution time 03 medical and health sciences 0302 clinical medicine Software Health Information Management distributed data networks Cox proportional hazards regression 030212 general & internal medicine privacy-protecting analytics Original Paper business.industry 030503 health policy & services distributed regression analysis Regression analysis Workflow File transfer Data mining 0305 other medical science business computer Analysis center |
| Zdroj: | JMIR Medical Informatics, Vol 8, Iss 6, p e15073 (2020) JMIR Medical Informatics |
| ISSN: | 2291-9694 |
| Popis: | Background A distributed data network approach combined with distributed regression analysis (DRA) can reduce the risk of disclosing sensitive individual and institutional information in multicenter studies. However, software that facilitates large-scale and efficient implementation of DRA is limited. Objective This study aimed to assess the precision and operational performance of a DRA application comprising a SAS-based DRA package and a file transfer workflow developed within the open-source distributed networking software PopMedNet in a horizontally partitioned distributed data network. Methods We executed the SAS-based DRA package to perform distributed linear, logistic, and Cox proportional hazards regression analysis on a real-world test case with 3 data partners. We used PopMedNet to iteratively and automatically transfer highly summarized information between the data partners and the analysis center. We compared the DRA results with the results from standard SAS procedures executed on the pooled individual-level dataset to evaluate the precision of the SAS-based DRA package. We computed the execution time of each step in the workflow to evaluate the operational performance of the PopMedNet-driven file transfer workflow. Results All DRA results were precise ( Conclusions We integrated a SAS-based DRA package with PopMedNet and successfully tested the new capability within an active distributed data network. The study demonstrated the validity and feasibility of using DRA to enable more privacy-protecting analysis in multicenter studies. |
| Databáze: | OpenAIRE |
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