Diversity in optical coherence tomography normative databases: moving beyond race

Abstract Normative databases of optical coherence tomography (OCT) metrics, such as retinal nerve fiber layer (RNFL) and macular thickness, are critical to clinical use of OCT imaging. In order to accurately represent the range of normal variation in patient populations, these normative databases mu...

Full description

Bibliographic Details
Main Authors: Nihaal Mehta, Nadia K. Waheed
Format: Article
Language:English
Published: BMC 2020-03-01
Series:International Journal of Retina and Vitreous
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40942-020-0208-5
_version_ 1819297822423384064
author Nihaal Mehta
Nadia K. Waheed
author_facet Nihaal Mehta
Nadia K. Waheed
author_sort Nihaal Mehta
collection DOAJ
description Abstract Normative databases of optical coherence tomography (OCT) metrics, such as retinal nerve fiber layer (RNFL) and macular thickness, are critical to clinical use of OCT imaging. In order to accurately represent the range of normal variation in patient populations, these normative databases must themselves be adequately diverse. Thus far, diversity in OCT normative databases has largely been defined as racial diversity. However, this has largely been based on self-reported “race,” which is inconsistent and generally not scientifically rigorous as a form of categorization. Moreover, there is a great deal of variation even within any single racial group, suggesting that other drivers of variation, such as geography or socioeconomic status, may be more important metrics for diversity. Finally, race itself is a proxy for the biological variation that must be represented in such samples, and as such racial diversity does not itself inherently equate to adequate biologic diversity. As clinical use of OCT continues to grow, including to international settings, it is increasingly important that normative databases built into OCT systems accurately represent the populations to which they are applied. Race is not an ideal sole or even primary means of assessing sample diversity in this context. In future normative OCT database construction, other forms of diversity should be considered.
first_indexed 2024-12-24T05:20:07Z
format Article
id doaj.art-ac9e3fc831b24fc39aa72c18b5bcc6c6
institution Directory Open Access Journal
issn 2056-9920
language English
last_indexed 2024-12-24T05:20:07Z
publishDate 2020-03-01
publisher BMC
record_format Article
series International Journal of Retina and Vitreous
spelling doaj.art-ac9e3fc831b24fc39aa72c18b5bcc6c62022-12-21T17:13:28ZengBMCInternational Journal of Retina and Vitreous2056-99202020-03-01611410.1186/s40942-020-0208-5Diversity in optical coherence tomography normative databases: moving beyond raceNihaal Mehta0Nadia K. Waheed1The Warren Alpert Medical School of Brown UniversityDepartment of Ophthalmology, New England Eye Center, Tufts Medical CenterAbstract Normative databases of optical coherence tomography (OCT) metrics, such as retinal nerve fiber layer (RNFL) and macular thickness, are critical to clinical use of OCT imaging. In order to accurately represent the range of normal variation in patient populations, these normative databases must themselves be adequately diverse. Thus far, diversity in OCT normative databases has largely been defined as racial diversity. However, this has largely been based on self-reported “race,” which is inconsistent and generally not scientifically rigorous as a form of categorization. Moreover, there is a great deal of variation even within any single racial group, suggesting that other drivers of variation, such as geography or socioeconomic status, may be more important metrics for diversity. Finally, race itself is a proxy for the biological variation that must be represented in such samples, and as such racial diversity does not itself inherently equate to adequate biologic diversity. As clinical use of OCT continues to grow, including to international settings, it is increasingly important that normative databases built into OCT systems accurately represent the populations to which they are applied. Race is not an ideal sole or even primary means of assessing sample diversity in this context. In future normative OCT database construction, other forms of diversity should be considered.http://link.springer.com/article/10.1186/s40942-020-0208-5Optical coherence tomographyNormative databaseRaceRace-based medicineDiversity
spellingShingle Nihaal Mehta
Nadia K. Waheed
Diversity in optical coherence tomography normative databases: moving beyond race
International Journal of Retina and Vitreous
Optical coherence tomography
Normative database
Race
Race-based medicine
Diversity
title Diversity in optical coherence tomography normative databases: moving beyond race
title_full Diversity in optical coherence tomography normative databases: moving beyond race
title_fullStr Diversity in optical coherence tomography normative databases: moving beyond race
title_full_unstemmed Diversity in optical coherence tomography normative databases: moving beyond race
title_short Diversity in optical coherence tomography normative databases: moving beyond race
title_sort diversity in optical coherence tomography normative databases moving beyond race
topic Optical coherence tomography
Normative database
Race
Race-based medicine
Diversity
url http://link.springer.com/article/10.1186/s40942-020-0208-5
work_keys_str_mv AT nihaalmehta diversityinopticalcoherencetomographynormativedatabasesmovingbeyondrace
AT nadiakwaheed diversityinopticalcoherencetomographynormativedatabasesmovingbeyondrace