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Record W3094350968 · doi:10.12788/cutis.0038

Psoriasis in Patients of Color: Differences in Morphology, Clinical Presentation, and Treatment

2020· review· en· W3094350968 on OpenAlexaffabout
Mathew N. Nicholas, Airiss R. Chan, Morvarid Hessami-Booshehri

Bibliographic record

VenueCutis · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsUniversity of TorontoWomen's College Hospital
Fundersnot available
KeywordsPsoriasisMedicineDermatologyPsychosocialPresentation (obstetrics)PopulationDiseasePathologySurgery

Abstract

fetched live from OpenAlex

Psoriasis is a chronic inflammatory skin disease affecting 2% to 3% of individuals worldwide.However, the majority of clinical data are in white patients, with limited data in patients of color.We present 3 cases of psoriasis representative of patients presenting to an urban and racially diverse hospital-based dermatology clinic in Toronto, Ontario, Canada, to illustrate the differences in psoriasis in patients of color compared to white patients.We review the differences in the morphology, presentation, treatment, and psychosocial impact of psoriasis in this population.We also discuss the importance of early diagnosis, treatment considerations, and education in dermatology training programs regarding psoriasis in patients of color.Cutis.2020;106(suppl 2):7-10. Psoriasis is a chronic inflammatory skin disease that affects 2% to 3% of individuals worldwide.1 Despite extensive research, the majority of clinical data are in white patients with limited data in patients of color, yet a number of differences are known.The prevalence of psoriasis differs among racial and ethnic groups, with lower prevalence in racial minorities. 2 A cross-sectional American study using data from 2009 through 2010 showed the prevalence for psoriasis was 3.6% in white patients, 1.9% in black patients, 1.6% in Hispanic patients, and 1.4% in other racial groups.3 Psoriasis presents differently in patients of color, both in morphology and severity.Cultural differences and stigma may contribute to the differences seen in severity but also to the psychological impact and treatment choices in patients of color compared to white patients.4 It has even been theorized that treatment efficacy could differ because of potential genetic differences.5 Psoriasis in patients of color is an emerging clinical issue that requires further attention so that dermatologists can learn about, diagnose, and treat them.We report 3 cases of patients of color with psoriasis who presented to an urban and racially diverse dermatology clinic affiliated with Scarborough General Hospital in Toronto, Ontario, Canada.A retrospective chart review was performed on these high-yield representative cases to demonstrate differences in color and morphology, disease severity, and treatment in patients of various races seen at our clinic.After informed consent was obtained, photographs were taken of patient cutaneous findings to illustrate these differences.Discussion with these selected patients yielded supplementary qualitative data, highlighting individual perspectives of their disease. Case SeriesPatient 1-A 53-year-old black man from Grenada presented to our clinic with a history of psoriasis for a number of years that presented as violaceous plaques throughout large portions of the body (Figure 1).He previously had Psoriasis in Patients of Color: Differences in Morphology, Clinical Presentation, and Treatment

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.349
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2020
Admission routes2
Has abstractyes

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