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Rethinking the use of population descriptors in dermatology trials and beyond: disentangling race and ethnicity from skin color

Archives of Dermatological Research (2025) 317:728

https://doi.org/10.1007/s00403-025-04219-6

CONSENSUS ARTICLE

RETHINKING THE USE OF POPULATION DESCRIPTORS IN DERMATOLOGY TRIALS AND BEYOND: DISENTANGLING RACE AND ETHNICITY FROM SKIN COLOR

Valerie M. Harvey 1

Jenna C. Lester2

Tarannum Jaleel3

Junko Takeshita4,5

Amy J. McMichael6

Yvette Miller-Monthrope7,8,9

Nina G. Jablonski10

Jade Lewis3

Andrew F. Alexis11

Stafford G. Brown12

Cheryl M. Burgess13

Angel S. Byrd14

Suephy C. Chen3,15

Caryn Cobb15

Roxana Daneshjou16

Seemal R. Desai17,18

Candrice R. Heath19

Chidubem A.V. Okeke20

Hema Sundaram21,22,23

Susan C. Taylor4

Jonathan S. Weiss24,25

Jane Y. Yoo26

Valerie D. Callender14,27

Received: 12 March 2025 / Revised: 12 March 2025 / Accepted: 2 April 2025 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025

ABSTRACT

Importance: Race and ethnicity as population descriptors in research and clinical practice have often been a subject of debate, drawing heightened scrutiny in recent years. Criticism focuses on their oversimplification and misapplication, which fail to capture the complexity of human health and genetic diversity. There is growing recognition that these categories, rooted in outdated social constructs, do not accurately reflect biological differences. Observations: Historically, race and ethnicity have been used as proxies for genetic variation and skin color, despite the understanding that these constructs are not biologically defined. The Skin of Color Society’s second Meeting the Challenge Summit, attended by over 100 U.S. and international participants, highlighted several key themes: (1) the need for transparency in the rationale behind using population descriptors and decision-making processes; (2) recognizing the role of race and racism in dermatology; (3) exploring the intersection of dermatology, skin color, and cultural influences; (4) understanding the context of population descriptor usage; (5) developing improved, objective tools for classifying skin color; and (6) advancing research and creating guidelines. Conclusions and Relevance: There is an urgent need to reconsider the use of race and ethnicity as population descriptors in dermatology research. Current systems, which conflate social identity with biological markers, perpetuate health disparities and limit the accuracy of clinical data. Moving forward, more specific descriptors such as skin color, alongside socially determined factors, will be crucial in achieving meaningful diversity and inclusivity in clinical research.

Race and ethnicity as population descriptors in research and clinical practice have often been a subject of debate, drawing heightened scrutiny in recent years [1, 2]. Current discourse highlights the imperative for clarity and transparency, and critiques the misuse of both race and ethnicity as descriptors through misclassification, oversimplification or decontextualization [3–5]. Critics of this discussion have also advocated for the exclusion of race and ethnicity from clinical care prediction models [6, 7] to make way for precision medicine with population descriptors that better reflect the complexities of human health [4, 5]. Population descriptors are defined as concepts or classification schemes that categorize people into groups based on perceived characteristics or dimensions of interest, such as gender, race, and ethnicity [4]. In 2023, the National

Academies of Sciences, Engineering and Medicine examined best practices for using population descriptors in genetics and genomics research. This seminal examination provided recommendations for the effective selection and application of these descriptors, emphasizing the need for a clear understanding of their context and a compelling rationale for their use, while recommending against the use of race as a proxy for genetic variance [4]. A 2024 report by the National Academies of Sciences, Engineering and Medicine has built upon and enriched these recommendations through a comprehensive assessment of race and ethnicity constructs in current biomedical research, providing instrumental guidance and appraisal of their future role in research [5].

PAST AND PRESENT: Race and ethnicity as population descriptors in dermatology

For centuries, discrimination tied to racial and ethnic groups has fostered racism in science and medicine. Deep-seated myths regarding differences in skin thickness based on racial categorization [8], as well as flawed attempts at categorizing differences in the perception of pain based on race [9], exemplify how racism and discriminatory behaviors have influenced dermatologic research and clinical decision making in adverse ways for generations. Eliminating the use of race and ethnicity as biologic indicators is essential for addressing health disparities and achieving meaningful diversity in dermatologic research studies. Additionally, these ongoing discussions regarding population descriptors in medicine must be disseminated to a broader audience.

The use of race and ethnicity as population descriptors is undoubtedly important for characterizing study populations, determining the generalizability of study findings, and identifying and understanding health disparities; [3, 10, 11] however, tethering biologic data solely to race and ethnicity risks erroneously implying biologic differences and reinforces a power dynamic that favors groups afforded greater social privilege, while disenfranchising the racially minoritized. There has been discourse around this approach not only exacerbating disparities in health outcomes, but also reinforcing misconceptions about genetic diversity [2, 12].

AN OVERVIEW OF SKIN CHARACTERIZATION IN RESEARCH

In dermatologic research, race and ethnicity continue to be used inappropriately as proxies for skin color and genetic ancestry; however, as constructs of social identity that are not defined biologically, they are poor surrogates for both cutaneous pigmentation and biologic variation [4]. Skin color is determined primarily by the content and distribution of melanin, a pigment produced by melanocytes within the epidermis. Eumelanin, the most abundant type of melanin in humans, imparts brown and black hues, whereas pheomelanin contributes reddishyellow tones. In addition to melanin, other smaller contributors to skin color include the level of hemoglobin in the dermal capillaries, and carotenoids obtained from the diet. It is the interplay between these factors that contributes to the vast scope of the

skin color spectrum [13, 14]. Race and ethnicity alone fail to capture the breadth of skin tones that exist both among and within groups [3].

The best classification method for characterizing skin color remains elusive [15] and existing skin-typing classification systems fail to portray the full phenotypic variance within the global population accurately [16]. Notably criticized is the Fitzpatrick skin phototype scale – the de facto gold standard of skin classification despite its welldocumented shortcomings [15]. Originally created to classify the photosensitivity of lighter skin tones when exposed to ultraviolet light, it was later amended to incorporate darker skin; [17] however, it has proven inadequate for this challenge through inherent biases in the scale conflating race, ethnicity, and skin color [15].

REPRESENTATION IN CLINICAL TRIALS

The limitations of current population descriptors and skin classification systems reflect the broader lack of diverse representation observed within medical research. Underrepresentation of populations in clinical trials can compromise the generalizability of research findings, leading to the development of diagnostic and therapeutic interventions with variable or unknown efficacy and/or unidentified safety concerns across different populations [10, 18, 19]. The limitations of pulse oximetry in accurately measuring oxygen saturation levels exemplify the consequences of inequitable design and calibration processes, which delayed life-saving therapy during the COVID-19 pandemic [20]. Pulse oximeters were validated by the U.S. Food and Drug Administration (FDA) without rigorous testing across a diverse range of skin tones; only two subjects, or 15% of the study pool, were required to have darkly pigmented skin [21]. Due to biased instrumentation, Black patients experienced nearly three times the rate of undetected occult hypoxemia [20] compared with White patients, leading to significant clinical differences and delays in critical care delivery. The consequences of inadequate diversity in research are also apparent in dermatology, where a recent study assessing the representation of

racial and ethnic minority groups in dermatology clinical trials found that only 38% of U.S. studies met the criterion for adequate diversity, defined as 20% minority participation (including participants of non-White race and Hispanic ethnicity) [22]. There is also a risk that the underrepresentation of certain populations perpetuates distrust, generates demographically unreliable datasets that are unsuitable for subanalyses, and limits artificial intelligence (AI)-driven drug design [23].

For example, AI tools developed from datasets that lack diversity fail when applied to diverse populations. A recent systematic review characterizing publicly available skin cancer image datasets identified a limited representation of ethnicities and Fitzpatrick skin types [24]. When tested on darker skin types, automated algorithms have less than half of the diagnostic accuracy than when tested on white skin [25]. Additionally, it is known that deep neural networks for classifying dermatologic images are not only biased against darker skinned individuals due to discrepancies in the dataset but also as a result of lower image contrast in these individuals [26].

MEETING THE CHALLENGE: Pathway to implementation of modified descriptors in dermatology

There is an urgent need to reconsider the use of population descriptors to ensure a rigorous rationale for their application. Given the ongoing efforts to diversify clinical trials, the meteoric advancements of AI in medicine, and the recent landmark recommendations from the National Academies of Sciences, Engineering and Medicine, challenging the current practice of utilizing race as a proxy for skin color in dermatology studies has never been more critical. In 2023, the Skin of Color Society hosted its second Meeting the Challenge Summit with over one hundred U.S. and international attendees. Dermatologists, anthropologists, geneticists, industry leaders, journal editors, and representatives from the National Institutes of Health and the FDA, examined the complexities of using race and ethnicity in dermatology research studies via presentations and expert-led roundtable discussions.

During the Summit, several key themes emerged from the roundtable discussions, including: (1) the need for transparency – providing a clear rationale for the utilization of population descriptors and decision-making processes, improving replicability; (2) the need to acknowledge the role of race and racism in dermatology; (3) the intersection of dermatology, skin color and cultural influences; (4) context for use of population descriptors; (5) the necessity for improved and objective tools for capturing skin color; and (6) the need for further research and guidelines. The majority of attendees favored the constructive and transparent use of race and ethnicity rather than their elimination.

Challenging the way skin color and race are currently integrated into dermatology research is essential. It is well recognized that objective measures of skin color correlate poorly with race and

ethnicity [15–17, 27], as individuals with the same skin color can be of different races or ethnicities [28]. As dermatologists, we occupy a unique position at the intersection of race and skin color, which provides us with a profound understanding of the influence of cutaneous pigmentation on health outcomes. We recognize that skin color is a salient characteristic influencing health outcomes related to the manifestation of skin cancer susceptibility, inflammation, pigmentary alteration and a myriad of societal issues related to skin color-based discrimination.

To minimize the risk of worsening racial disparities [7], race and ethnicity should not be interpreted as proxies for skin color [29]. Further, utilizing contextual factors, such as socioeconomic and healthcare status, may reduce the risk of embedding prejudices into medical care [8]. If and when race and ethnicity are used, transparency in reporting is essential; individuals should be able to self-identify appropriately.

As we expand population descriptors to include skin color, clinicians and researchers must tailor their use to ensure clinical trial equity – a practice that is beginning to gain momentum [30]. In addition, guidelines should be developed and implemented carefully to complement race and ethnicity reporting in clinical research protocols [28, 31], while funding agencies and regulatory bodies will need to ensure that researchers are held accountable to a sufficient degree in terms of reporting transparently. To aid in data aggregation and harmonization, an explanation of classificatory criteria may also be required to avoid the loss of historic data [4].

CALL TO ACTION

Race and ethnicity, often used as surrogates for skin color and genetic ancestry in clinical trials and research studies, fall short as population descriptors due to their lack of specificity [4]. To improve diversity and representation in clinical trials, and to ensure meaningful translation of data into clinical practice, researchers need transparent, well-defined population descriptors with greater precision [4]. When developing and implementing more

inclusive population descriptors, there are multiple considerations. We must aim to promote inclusivity without an onerous number of subclassifications. We must formulate strategies to minimize additional economic and regulatory burdens posed by modified population descriptors. We must also aim to create consensus around standardized guidelines for the transparent, formalized use of datasets in machine learning protocols and other applications.

SUMMARY

Including skin color as a precise population descriptor could enhance representation significantly. Adopting and integrating more accurate and universally accepted descriptors in clinical practice and research represents a critical and attainable

goal. In summary, while there are challenges and controversies associated with the modification of population descriptors, there is an urgent need for a new paradigm.

ACKNOWLEDGEMENTS

We acknowledge Laura Preece, MSc and Rachel Byrne MSc of Ogilvy Health UK for their editorial assistance.

AUTHOR CONTRIBUTIONS

Made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; or the creation of new software used in the work: VMH, VC, JC, TJ, JT, AJM, YM, NJ, JL, HS. Drafted the work or revised it critically for important intellectual content: VMH, VC, JC, TJ, JT, AJM, YM, NJ, JL, HS. Approved the version to be published: All authors. Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: All authors.

DATA AVAILABILITY

No datasets were generated or analysed during the current study.

DECLARATIONS

Competing interests VMH serves as a consultant for AbbVie, Bristol Myers Squibb, Janssen, Johnson & Johnson, and L’Oréal, receiving honoraria; and serves as an advisory board member for SkinCeuticals, receiving honoraria. JCL serves as a consultant for Google and L’Oréal and an advisory board member for Mattice Biosciences. TJ serves as a principal investigator for UCB; receives research fellow support from Pfizer Inc., via the Skin of Color Grant, and from UCB; and serves as a consultant for Eli Lilly, Novartis, and UCB, receiving honoraria. JT serves as a consultant for Incyte Corporation, receiving honoraria; and receives research grants from Pfizer Inc., and Bristol Myers Squibb (paid to the Trustees of the University of Pennsylvania). AJM has received research grants from Concert, Procter & Gamble, Incyte, Revian; serves as a consultant to Lilly, Janssen, Pfizer, Arcutis, Almirall, AbbVie, CeraVe, Galderma, Bristol Myers Squibb, Sanofi Regeneron, Sun Pharma, UCB, Procter & Gamble, Revian, Johnson &

Johnson, L’Oréal, Leo, receiving honoraria; and has received royalties from Informa/Taylor and Francis, and McGraw Hill. YMM serves as an advisory board member for AbbVie, Bristol Myers Squibb, Boehringer Ingelheim, Fresenius Kabi, Incyte Corporation, Janssen, L’Oréal, Sanofi, Sun Pharma, Novartis, and UCB, receiving honoraria; and serves as a consultant for AbbVie, L’Oréal, and Galderma Laboratories, L.P., receiving honoraria. NGJ serves as an advisory board member for L’Oréal, receiving honoraria. JL has no relevant conflicts of interest to disclose. AFA is a consultant for AbbVie, Allergan, Almirall, Alphyn, Amgen, Apogee, Arcutis, Avita Medical, Bausch health, Beiersdorf, BMS, Canfield, Cara, Castle, Cutera, Dermavant, Eli Lilly, EPI, Galderma, Genentech, Genzyme, Incyte, Janssen, Leo, L’Oréal, Ortho, Pfizer, Sanofi-Regeneron, Swiss American, UCB and VisualDx, a speaker for BMS, J&J, Janssen, Regeneron and Sanofi-Genzyme, receives equipment from Aerolase, grants from AbbVie, Amgen, Arcutis, Castle, Dermavant, Galderma and Leo, and royalties

from Elsevier, Springer, Wiley-Blackwell and Wolters Kluwer Health. SGB has no relevant conflicts of interest to disclose. CMB has no relevant conflicts of interest to disclose. ASB is the inaugural recipient of the Skin of Color Society Career Development Award, as well as the Society for Investigative Dermatology Freinkel Diversity Fellowship Award, and a recipient of the Robert A. Winn Diversity in Clinical Trials Career Development Award (Winn CDA) funded by Bristol Myers Squibb Foundation (BMSF); serves as a consultant for Senté, Inc. and Sonoma Biotherapeutics; and serves as an advisory board member for Novartis, receiving honoraria. SCC has no relevant conflicts of interest to disclose. CBCC has no relevant conflicts of interest to disclose. RD reported stock options from Revea and MDalgorithims, as well as personal fees from Pfizer, Frazier Healthcare Partners, and L’Oréal; and has a patent for 17/937 714 pending. SRD has no relevant conflicts of interest to disclose. CRH is a consultant for Arcutis, Apogee, Avita, Dermavant, Lilly, Janssen, Johnson and Johnson, Kenvue Pfizer, Regeneron, Sanofi, L’Oréal, Nutrafol, and WebMD. Investigator/ Research/Research Development Funding paid to institution: Eli Lilly and Company, CorEvitas, Janssen, Robert A. Winn Diversity in Clinical Trials Award Program established by the Bristol Meyers Squibb Foundation, and recipient of a Skin of Color Society Career Development Award. CAVO has no relevant conflicts of interest to disclose. HS has no relevant conflicts of interest to disclose. SCT is a past employee of Mercer Strategies and was on the board of directors; serves as a consultant to Arcutis Biotherapeutics, Inc, Beiersdorf, Inc., Bristol Myers Squibb, Cara Therapeutics, Dior, and Sanofi, receiving honoraria; serves as a consultant to Armis Biopharma, GloGetter, and Piction Health, receiving stock options; serves as an advisory board member for AbbVie, Avita Medical, Beiersdorf, Inc., Biorez, Inc., Eli Lilly, EPI Health, Evolus, Inc., Galderma Laboratories, L.P., Hugel

America, Inc., Incyte, Johnson & Johnson Consumer Products Company, L’Oréal USA, Medscape/WebMD, Pfizer, Scientis US, UCB, and Vichy Laboratories, receiving honoraria; serves as a speaker for Beiersdorf, Inc, Catalyst Medical Education LLC, LearnSkin, Medscape/WebMD, and MJH LifeSciences; has received royalties from McGraw Hill; is an investigator for Allergan Aesthetics, Concert Pharmaceuticals/ Sun Pharma, Croma-Pharma GmbH, Eli Lilly, and Pfizer, receiving grants and research funding; and serves on the editorial board for Practical Dermatology, Cutis, and Archives in Dermatologic Research, and as a peer-reviewer for British Journal of Dermatology. JSW serves as an advisory board member for Bristol Myers Squibb, Dermavant Sciences, Foamix, Galderma Laboratories, L.P., Incyte Corporation, Novartis, and UCB receiving honoraria; serves as a consultant for Arcutis,Inc., Biofrontera, Cutera, Inc., Leo Pharma Inc, Ortho Dermatologics, and UCB, receiving fees or honoraria; is an investigator for AbbVie, Bausch Health, Biofrontera, Bristol Myers Squibb, Cutera, Inc., Dermavant Sciences, Foamix, Galderma Laboratories, L.P., Leo Pharma, Mindera, Moberg Pharma North America LLC, Novartis, Palvella Therapeutics, and Verrica Pharmaceuticals Inc., receiving grants and research funding; and serves as a speaker for AbbVie, Arcutis, Inc., Galderma Laboratories, L.P., Ortho Dermatologics, Regeneron, and Sanofi Genzyme, receiving honoraria. JY has no relevant conflicts of interest to disclose. VDC serves as a researcher for Avava, Galderma, I Know Skincare, Janssen, Prollenium, Skinbetter Science, Symatese, and Teoxane; serves as a researcher/consultant for AbbVie/ Allergan, Incyte, L’Oréal Aesthetics, and Pfizer; serves as a consultant for Acne Store, Aerolase, Avita Medical, Beiersdorf, Cutera, Dermavant, Juenes Aesthetics, Orthoderm, and SkinCeuticals; serves as a consultant/ speaker for Arcutis; serves as a researcher/consultant/ speaker for Eli Lilly; and has received royalties from UpToDate.

REFERENCES

1. Byeon YJJ, Islamaj R, Yeganova L et al (2021) Evolving use of ancestry, ethnicity, and race in genetics research – a survey spanning seven decades. Am J Hum Genet 108:2215–2223

2. Mauro M, Allen DS, Dauda B, Molina SJ, Neale BM, Lewis ACF (2022) A scoping review of guidelines for the use of race, ethnicity, and ancestry reveals widespread consensus but also points of ongoing disagreement. Am J Hum Genet 109:2110–2125

3. Flanagin A, Frey T, Christiansen SL (2021) Updated guidance on the reporting of race and ethnicity in medical and science journals. JAMA 326:621–627

4. A consensus study report of The National Academies of Sciences, Engineering and Medicine (2023) Using population descriptors in genetics and genomics research: a new framework for an evolving field. National Academies, Washington, DC. h t t p s : / / d o i . o r g / 1 0 . 1 7 2 2 6 / 2 6 9 0 2 )

5. A consensus study report of The National Academies of Sciences (2024) Engineering and medicine. Rethinking race and ethnicity in biomedical research. National Academies, Washington, DC. h t t p s : / / d o i . o r g / 1 0 . 1 7 2 2 6 / 2 7 9 1 3 )

6. Cerdeña JP, Plaisime MV, Tsai J (2020) From racebased to raceconscious medicine: how anti-racist uprisings call Us to act. Lancet 396:1125–1128

7. Vyas DA, Eisenstein LG, Jones DS (2020) Hidden in plain sight – reconsidering the use of race correction in clinical algorithms. N Engl J Med 383:874–882

8. Sadeghi NB, Adamson AS (2024) The problematic legacy of skin-thickness measurement in race-based dermatology research. JAMA Dermatol 160:143–144

9. Hoffman KM, Trawalter S, Axt JR, Oliver MN (2016) Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between Blacks and Whites. Proc Natl Acad Sci U S A 113:4296–4301

10. A consensus study report of The National Academies of Sciences, Engineering and Medicine (2022) Improving representation in clinical trials and research: Building research equity for women and underrepresented groups. National Academies, Washington, DC. h t t p s : / / d o i . o r g / 1 0 . 1 7 2 2 6 / 2 6 4 7 9 )

11. Okeke CAV, Perry JD, Simmonds FC et al (2022) Clinical trials and skin of color: the example of hidradenitis suppurativa. Dermatology 238:180–184

12. Jablonski NG (2021) Skin color and race. Am J Phys Anthropol 175:437–447

13. Alaluf S, Heinrich U, Stahl W, Tronnier H, Wiseman S (2002) Dietary carotenoids contribute to normal human skin color and UV photosensitivity. J Nutr 132:399–403

14. Taylor SC (2002) Skin of color: biology, structure, function, and implications for dermatologic disease. J Am Acad Dermatol 46:S41–S62

15. Harvey VM, Alexis A, Okeke CAV et al (2024) Integrating skin color assessments into clinical practice and research: a review of current approaches. J Am Acad Dermatol 91:1189–1198

16. Goon P, Banfield C, Bello O, Levell NJ (2021) Skin cancers in skin types IV–VI: does the Fitzpatrick scale give a false sense of security? Skin Health Dis 1:e40

17. Chan JL, Ehrlich A, Lawrence RC, Moshell AN, Turner ML, Kimball AB (2005) Assessing the role of race in quantitative measures of skin pigmentation and clinical assessments of photosensitivity. J Am Acad Dermatol 52:609–615

18. Ramamoorthy A, Pacanowski MA, Bull J, Zhang L (2015) Racial/ethnic differences in drug disposition and response: review of recently approved drugs. Clin Pharmacol Ther 97:263–273

19. Mineroff J, Nguyen JK, Jagdeo J (2023) Racial and ethnic underrepresentation in dermatology clinical trials. J Am Acad Dermatol 89:293–300

20. Sjoding MW, Dickson RP, Iwashyna TJ, Gay SE, Valley TS (2020) Racial bias in pulse oximetry measurement. N Engl J Med 383:2477–2478

21. Pulse oximeters – premarket notification submissions [510(k)s]: guidance for industry and Food and Drug Administration staff. 1. Byeon YJJ Rockville, MD: Food and Drug Administration, March 4, 2013. (

race/ethnicity: skin color, gender, and the health of young adults in the United States. Popul Res Policy Rev 38:271–299

28. Bissonnette R, Jankicevic J, Saint-Cyr Proulx E, Maari C (2023) Ethnicity, race and skin color: challenges and opportunities for atopic dermatitis clinical trials. J Clin Med 12:3805

29. Borrell LN, Elhawary JR, Fuentes-Afflick E et al (2021) Race and genetic ancestry in medicine – a time for reckoning with racism. N Engl J Med 384:474–480

22. Chen V, Akhtar S, Zheng C, Kumaresan V, Nouri K (2022) Assessment of changes in diversity in dermatology clinical trials between 2010–2015 and 2015–2020: a systematic review. JAMA Dermatol 158:288–292

23. Ng MY, Youssef A, Miner AS et al (2023) Perceptions of data set experts on important characteristics of health data sets ready for machine learning: a qualitative study. JAMA Netw Open 6:e2345892

24. Wen D, Khan SM, Ji Xu A et al (2022) Characteristics of publicly available skin cancer image datasets: a systematic review. Lancet Digit Health 4:e64–e74

25. Kamulegeya L, Bwanika J, Okello M et al (2023) Using artificial intelligence on dermatology conditions in Uganda: a case for diversity in training data sets for machine learning. Afr Health Sci 23:753–763

26. Benčević M, Habijan M, Galić I, Babin D, Pižurica A (2024) Understanding skin color bias in deep learning-based skin lesion segmentation. Comput Methods Programs Biomed 245:108044

27. Perreira KM, Wassink J, Harris KM (2019) Beyond

30. FDA guidance provides new details on diversity action plans required for certain clinical studies Silver Spring, MD: Food and Drug Administration, June 26, 2024. ( h t t p s : / / w w w . f

31. Chung HJ, Jablon K, Dawkins O, Richardson M, Ho JD (2023) The frequency of reporting race, ethnicity, and skin phototypes in dermatology case reports. JAAD Int 12:39–41

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AUTHORS AND AFFILIATIONS

Valerie M. Harvey 1

Jenna C. Lester2

Tarannum Jaleel3

Junko Takeshita4,5

Amy J. McMichael6

Yvette Miller-Monthrope7,8,9

Nina G. Jablonski10

Jade Lewis3

Andrew F. Alexis11

Stafford G. Brown12

Cheryl M. Burgess13

Angel S. Byrd14

Suephy C. Chen3,15

Caryn Cobb15

Roxana Daneshjou16

Seemal R. Desai17,18

Candrice R. Heath19

Chidubem A.V. Okeke20

Hema Sundaram21,22,23

Susan C. Taylor4

Jonathan S. Weiss24,25

Jane Y. Yoo26

Valerie D. Callender14,27

Valerie M. Harvey valerie.harvey@tpmgpc.com

1. Hampton Roads Center for Dermatology, Virginia Beach, VA, USA

2. Department of Dermatology, University of California San Francisco, San Francisco, CA, USA

3. Department of Dermatology, Duke University School of Medicine, Durham, NC, USA

4. Department of Dermatology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

5. Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

6. Department of Dermatology, Wake Forest University School of Medicine, Winston Salem, NC, USA

7. Division of Dermatology, Department of Medicine, University of Toronto, Toronto, ON, Canada

8. Division of Dermatology, Women’s College Hospital, University of Toronto, Toronto, ON, Canada

9. Department of Laboratory Medicine, University Health Network, University of Toronto, Toronto, ON, Canada

10. Department of Anthropology, The Pennsylvania State University, University Park, PA, USA

11. Israel Englander Department of Dermatology, Weill Cornell Medical College, New York, NY, USA

12. Division of Dermatology, Washington University, St. Louis, MO, USA

13. Center for Dermatology and Dermatologic Surgery, Washington, D.C. , USA

14. Department of Dermatology, Howard University College of Medicine, Washington, D.C. , USA

15. Mount Auburn Hospital, Harvard Medical School, Cambridge, MA, USA

16. Department of Biomedical Data Science and Dermatology, Stanford School of Medicine, Stanford, CA, USA

17. Department of Dermatology, University of Texas, Southwestern Medical Center, Dallas, TX, USA

18. Innovative Dermatology, Plano, TX, USA

19. Department of Urban Health and Population Science, Center for Urban Bioethics, The Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA

20. Department of Dermatology, Howard University College of Medicine, Washington, DC, USA

21. Dermatology, Cosmetic & Laser Surgery, Rockville, MD, USA

22. Dermatology, Cosmetic & Laser Surgery, Fairfax, VA, USA

23. Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, University of Manchester, Manchester, UK

24. Department of Dermatology, Emory University School of Medicine, Atlanta, GA, USA

25. Georgia Dermatology Partners, Snellville, GA, USA

26. Icahn School of Medicine at Mount Sinai, New York, NY, USA

27. Callender Dermatology & Cosmetic Center, Glenn Dale, MD, USA