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使入组的试验参与者与疾病人口统计学特征相匹配:利用向机构审查委员会提交的材料来确定研究人员培训的机会。

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

作者信息

Eckstrom Elizabeth, Zauflik Meredith, De Lima Bryanna

机构信息

Division of General Internal Medicine & Geriatrics, Department of Medicine, Oregon Health & Science University, Portland, OR, USA.

Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, OR, USA.

出版信息

J Clin Transl Sci. 2023 May 8;7(1):e114. doi: 10.1017/cts.2023.539. eCollection 2023.

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.

摘要

背景

许多疾病在老年人中高度流行,但老年人在相应试验中的代表性往往不足。我们的目标是:(1)确定2019年美国国立卫生研究院(NIH)寿命政策实施前后,机构审查委员会(IRB)方案年龄范围与入组人口统计学数据和疾病人口统计学数据之间的一致性;(2)提高主要研究者(PI)对包容性招募的认识。

方法

这是一项前后对照研究。我们回顾了2017年至2018年在俄勒冈健康与科学大学符合入选标准的研究者发起的研究,以确定基线一致性。一致性由方案/入组年龄与疾病人口统计学数据的匹配程度定义:完全匹配得2分,部分匹配得1分,不匹配得0分。在NIH政策实施后,我们审查新研究的一致性。当确定存在不匹配时,我们联系PI(在IRB方案初次提交时或在持续招募期间)以提高认识,并提供在其试验中扩大纳入老年人的策略。

结果

将IRB方案年龄与疾病人口统计学数据相匹配的研究从实施前的78%显著提高到实施后的91.2%。同样,实施后研究入组年龄与疾病人口统计学数据的匹配度提高了13.4%(从74.5%提高到87.9%)。在实施后18项不匹配的研究中,7名PI接受了会面,其中3名随后更改了他们的方案年龄范围。

结论

本研究强调了转化研究所和学术机构可用于识别参与者与疾病人口统计学数据不匹配的研究的策略,为提高研究者认识和培训以增强包容性提供了机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb7a/10260342/b10dc589efe0/S2059866123005393_fig1.jpg

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