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Journal ArticleDOI: 10.1111/BJD.19932

Equity in skin typing: why it's time to replace the Fitzpatrick scale

05 Mar 2021-British Journal of Dermatology (John Wiley & Sons, Ltd)-Vol. 185, Iss: 1, pp 198-199
Abstract: Dermatologists of color have long championed skin of color representation in education and workforce diversity. For health equity, we must reconsider even fundamental and accepted terminology. The Fitzpatrick skin type (FST) scale, with both disproportionate focus on white skin tones and inconsistent use, perpetuates skin color bias. Indeed, since FST does not purely objectively estimate skin pigmentation, it may inaccurately assess patients regarding risks for skin cancer and from interventions. Dermatology must seek an objective classification system, and given the rise of artificial intelligence (AI), technology-based approaches may be solutions.

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Topics: Fitzpatrick scale (64%)
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Open accessJournal ArticleDOI: 10.1111/BJD.20473
Abstract: Dermatology publications have substantial untapped potential to improve patient care for all patients and communities. The leadership role of both editors and editorial boards of these journals, books, and digital media provides an important opportunity to support professional diversity, equity, and inclusion (DEI) plus democratization of knowledge.1 Multiple events in many countries in recent times have revealed the need to work harder at DEI to ensure a level playing field for all patients, clinicians, and researchers.

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Topics: Level playing field (50%)

1 Citations


Open accessJournal ArticleDOI: 10.1111/JOCD.14435
Abstract: Dermatology publications have substantial untapped potential to improve patient care for all patients and communities. The leadership role of both editors and editorial boards of these journals, books, and digital media provides an important opportunity to support professional diversity, equity, and inclusion (DEI) plus democratization of knowledge.1 Multiple events in many countries in recent times have revealed the need to work harder at DEI to ensure a level playing field for all patients, clinicians, and researchers.

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Topics: Level playing field (50%)


Open accessPosted Content
Abstract: More than 3 billion people lack access to care for skin disease. AI diagnostic tools may aid in early skin cancer detection; however most models have not been assessed on images of diverse skin tones or uncommon diseases. To address this, we curated the Diverse Dermatology Images (DDI) dataset - the first publicly available, pathologically confirmed images featuring diverse skin tones. We show that state-of-the-art dermatology AI models perform substantially worse on DDI, with ROC-AUC dropping 29-40 percent compared to the models' original results. We find that dark skin tones and uncommon diseases, which are well represented in the DDI dataset, lead to performance drop-offs. Additionally, we show that state-of-the-art robust training methods cannot correct for these biases without diverse training data. Our findings identify important weaknesses and biases in dermatology AI that need to be addressed to ensure reliable application to diverse patients and across all disease.

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Open accessJournal ArticleDOI: 10.1001/JAMADERMATOL.2013.6101
Steven Eilers1, Daniel Q. Bach1, Rikki Gaber1, Hanz Blatt1  +4 moreInstitutions (1)
01 Nov 2013-JAMA Dermatology
Abstract: Importance Determining Fitzpatrick skin phototypes (FST) allows physicians to assess a person’s risk of developing sunburn and, by extension, the need for sun protection to prevent the development of skin cancer. Reflectance spectrophotometry objectively measures the melanin index and can assist in determining the accuracy of self-report of FST compared with dermatologist-determined FST. Objectives To assess whether self-reported or dermatologist-determined FST is more accurate in identifying a participant’s FST for FST I through VI and to assess the relevance of the burning and tanning measures for a range of skin types among ethnically diverse participants. Design and Setting A convenience sample of participants in an observational study from June 2, 2010, through December 15, 2010, at an ambulatory academic dermatologic practice and employee health center in an urban city. Participants Participants, staff, and students of Northwestern University, who self-identified as being non-Hispanic white, Hispanic or Latino, Asian or Pacific Islander, or black. Main Outcomes and Measures Melanin index as measured with reflectance spectrophotometry compared with dermatologist- and participant-determined FST. Results Forty-two percent (114 of 270) of the participants’ responses to the burning and tanning questions could not be classified using standard FST definitions. The spectrophotometry measurements for dermatologist-determined FST were significantly different for FST III and IV ( P P P P = .90). Participant responses to burning and the dermatologist-determined FST were significantly correlated (Spearman ρ, 0.764; P P = .15). Spectrophotometry measurements assessing FST were statistically significantly different for FST III through VI ( P Conclusions and Relevance Dermatologist-determined FST is more accurate than self-report for FST III through VI. Rephrasing the questions using specific descriptors that have meaning to people with skin of color, such as skin irritation, tenderness, itching, or skin becoming darker, may allow physicians to more accurately assign a skin phototype and, by inference, assess the risk of these participants developing skin cancer. Trial Registration clinicaltrials.gov Identifier:NCT01124513

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Topics: Pacific islanders (50%)

84 Citations


Open accessJournal ArticleDOI: 10.1016/J.JAAD.2014.05.023
Abstract: Background Fitzpatrick skin phototype (FSPT) is the most common method used to assess sunburn risk and is an independent predictor of skin cancer risk. Because of a conventional assumption that FSPT is predictable based on pigmentary phenotypes, physicians frequently estimate FSPT based on patient appearance. Objective We sought to determine the degree to which self-reported race and pigmentary phenotypes are predictive of FSPT in a large, ethnically diverse population. Methods A cross-sectional survey collected responses from 3386 individuals regarding self-reported FSPT, pigmentary phenotypes, race, age, and sex. Univariate and multivariate logistic regression analyses were performed to determine variables that significantly predict FSPT. Results Race, sex, skin color, eye color, and hair color are significant but weak independent predictors of FSPT ( P Limitations Our study enriched for responses from ethnic minorities and does not fully represent the demographics of the US population. Conclusions Patient self-reported race and pigmentary phenotypes are inaccurate predictors of sun sensitivity as defined by FSPT. There are limitations to using patient-reported race and appearance in predicting individual sunburn risk.

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Topics: Population (52%)

48 Citations



Journal ArticleDOI: 10.1016/J.CLINDERMATOL.2019.07.010
Vishal Gupta1, Vinod Sharma1Institutions (1)
Abstract: Skin phototyping refers to a skin classification scheme based on how the skin responds to sun exposure. The Fitzpatrick classification is the most widely accepted method of skin phototyping, based on a person's tendency to sunburn and ability to tan. Apart from estimating the initial therapeutic dose of UV light, skin phototyping is also useful in predicting the risk of photodamage and skin cancer and the outcome of esthetic procedures. Techniques to type the skin objectively have been developed to address the deficiencies associated with the subjective Fitzpatrick classification. Some skin typing systems have been proposed specifically to predict the response of skin to cosmetic procedures such as chemical peeling and laser resurfacing. We discuss the concept of skin type and its relation to skin color, as well as critically appraising the various available methods of skin typing.

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Topics: Skin Classification Scheme (68%), Skin cancer (56%), Sunburn (55%)

25 Citations