Matching enrolled trial participants to disease demographics: Using IRB submissions to identify opportunities for researcher training

Autor: Elizabeth Eckstrom, Meredith Zauflik, Bryanna De Lima
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Journal of Clinical and Translational Science, Vol 7 (2023)
Druh dokumentu: article
ISSN: 2059-8661
DOI: 10.1017/cts.2023.539
Popis: Abstract Background: Many diseases are highly prevalent in older adults, yet older adults are often underrepresented in corresponding trials. Our objectives were to (1) determine alignment between Institutional Review Board (IRB) protocol age ranges and enrollment demographics to disease demographics pre- and post-implementation of the 2019 National Institutes of Health (NIH) Lifespan Policy and (2) raise awareness about inclusive recruitment to principal investigators (PIs). Methods: This was a pre-post study. We reviewed investigator-initiated studies meeting eligibility criteria at Oregon Health & Science University from 2017 to 2018 to determine baseline alignment. Alignment was defined by the level of matching between protocol/enrollment age and disease demographics: 2 points for full match, 1 point for partial match, and 0 points for mismatch. After the NIH policy implementation, we reviewed new studies for alignment. When a mismatch was determined, we contacted PIs (either at initial IRB protocol submission or during ongoing recruitment) to raise awareness and provide strategies to expand inclusion of older adults in their trials. Results: Studies that matched IRB protocol ages to disease demographics significantly improved from 78% pre-implementation to 91.2% post-implementation. Similarly, study enrollment ages matching disease demographics increased by 13.4% following the implementation (74.5%–87.9%). Out of 18 post-implementation mismatched studies, 7 PIs accepted a meeting and 3 subsequently changed their protocol age ranges. Conclusion: This study highlights strategies that translational institutes and academic institutions could use to identify research studies whose participants do not align with disease demographics, offering opportunities for researcher awareness and training to enhance inclusion.
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