A Two-Stage Meta-Regression Framework for Precision Medicine Using Data from Clinical Data Research Networks
Study Dates
Last Modified
Tags
Publisher
Abstract
Study to develop evidence synthesis methods to improve distributed analyses in distributed research networks (DRN) and advance our understanding of benefit and risk of different treatment options.
Affiliation(s)
Funder(s)
Provenance
Description
Pediatric Crohn"s Disease (PCD) is a chronic inflammatory bowel disease (IBD) that has been recognized as one of the most important chronic diseases that affect children and adolescents, with increasing incidence in youth of varying ages. Literature presents gaps in understanding how to synthesize partial or pieces of evidence from multiple sites using distributed analysis for comparison of multiple treatments with respect to multiple patient-centered outcomes and how to better identify covariates that contribute to heterogeneous treatment effect (HTE) using data from distributed research networks (DRN).
In this study, the research team is to develop evidence synthesis methods to improve distributed analyses in DRN and to advance understanding of the benefits and risks of different treatment options. The methods aim to expand the scope and patient-centeredness of research using data from clinical data research networks (CDRNs).
Study Aims
Develop a novel meta-analytic modeling framework for synthesis of evidence from multiple sites to inform comparison of multiple treatments with respect to multiple patient-centered outcomes; develop a two-stage procedure within the proposed modeling framework for identification of HTE of treatments; validate and evaluate the proposed methods using EHR data from PCD patients in the Penn-CHOP IBD center and disseminate the methods to the PEDSnet consortium.
Development Code
Vocabulary
Clinical Subjects Headings
Creative Commons license
