Pulmonary and Critical Care Medicine Division, Department of Medicine, Morehouse School of Medicine, Atlanta, GA, USA.
Clinical Research Center, Morehouse School of Medicine, Atlanta, GA, USA.
Int J Chron Obstruct Pulmon Dis. 2024 Apr 29;19:969-980. doi: 10.2147/COPD.S430249. eCollection 2024.
Increasing evidence suggests that the inclusion of self-identified race in clinical decision algorithms may perpetuate longstanding inequities. Until recently, most pulmonary function tests utilized separate reference equations that are race/ethnicity based.
We assess the magnitude and scope of the available literature on the negative impact of race-based pulmonary function prediction equations on relevant outcomes in African Americans with COPD.
We performed a scoping review utilizing an English language search on PubMed/Medline, Embase, Scopus, and Web of Science in September 2022 and updated it in December 2023. We searched for publications regarding the effect of race-specific vs race-neutral, race-free, or race-reversed lung function testing algorithms on the diagnosis of COPD and COPD-related physiologic and functional measures. Joanna Briggs Institute (JBI) guidelines were utilized for this scoping review. Eligibility criteria: The search was restricted to adults with COPD. We excluded publications on other lung disorders, non-English language publications, or studies that did not include African Americans. The search identified publications. Ultimately, six peer-reviewed publications and four conference abstracts were selected for this review.
Removal of race from lung function prediction equations often had opposite effects in African Americans and Whites, specifically regarding the severity of lung function impairment. Symptoms and objective findings were better aligned when race-specific reference values were not used. Race-neutral prediction algorithms uniformly resulted in reclassifying severity in the African Americans studied.
The limited literature does not support the use of race-based lung function prediction equations. However, this assertion does not provide guidance for every specific clinical situation. For African Americans with COPD, the use of race-based prediction equations appears to fall short in enhancing diagnostic accuracy, classifying severity of impairment, or predicting subsequent clinical events. We do not have information comparing race-neutral vs race-based algorithms on prediction of progression of COPD. We conclude that the elimination of race-based reference values potentially reduces underestimation of disease severity in African Americans with COPD.
越来越多的证据表明,将自我认定的种族纳入临床决策算法可能会延续长期存在的不平等。直到最近,大多数肺功能测试都使用了基于种族/民族的单独参考方程。
我们评估了关于种族为基础的肺功能预测方程对 COPD 非裔美国人相关结局的负面影响的现有文献的规模和范围。
我们在 2022 年 9 月利用 PubMed/Medline、Embase、Scopus 和 Web of Science 进行了英语搜索,并在 2023 年 12 月进行了更新,进行了范围综述。我们搜索了关于种族特异性与种族中性、无种族或种族反转的肺功能测试算法对 COPD 诊断和 COPD 相关生理和功能测量的影响的出版物。本范围综述采用了乔安娜·布里格斯研究所(JBI)指南。纳入标准:搜索仅限于 COPD 成人。我们排除了其他肺部疾病、非英语语言出版物或未包括非裔美国人的研究。搜索确定了出版物。最终,选择了六篇同行评议的出版物和四篇会议摘要进行综述。
从肺功能预测方程中去除种族通常会对非裔美国人和白人产生相反的影响,特别是在肺功能损伤的严重程度方面。当不使用特定种族的参考值时,症状和客观发现更能协调一致。种族中性的预测算法统一导致研究中的非裔美国人的严重程度重新分类。
有限的文献不支持使用基于种族的肺功能预测方程。然而,这一说法并不能为每一种具体的临床情况提供指导。对于 COPD 的非裔美国人,使用基于种族的预测方程似乎在提高诊断准确性、分类损伤严重程度或预测后续临床事件方面效果不佳。我们没有比较基于种族的预测算法与基于种族的算法对 COPD 进展预测的信息。我们得出的结论是,消除基于种族的参考值可能会减少对 COPD 非裔美国人疾病严重程度的低估。