Racial and Ethnic Differences in Sociodemographic, Clinical, and Treatment Characteristics Among Patients with Atopic Dermatitis in the United States and Canada: Real-World Data from the CorEvitas Atopic Dermatitis Registry
Bibliographic record
Abstract
INTRODUCTION: This real-world, cross-sectional study compared sociodemographic, clinical and treatment characteristics, and patient-reported outcomes (PROs) among racial/ethnic groups in patients with atopic dermatitis (AD) who are candidates for systemic therapy. METHODS: ≥ 3 and Eczema Area and Severity Index [EASI] ≥ 12) at enrollment. Patients were categorized into five mutually exclusive racial/ethnic groups: non-Hispanic White, Black, Asian, Other/Multiracial, and Hispanic (any race). Patient, clinical, and treatment characteristics were captured at enrollment. Differences in means or proportions of characteristics among racial/ethnic groups were descriptively summarized using effect sizes. Adjusted prevalence ratios and mean differences were estimated (White race/ethnicity group as the reference category) with 95% confidence intervals (CI). RESULTS: Among 1288 patients, 64% (n = 822) were White, 13% (n = 167) Black, 10% (n = 129) Asian, 8% (n = 97) Hispanic, and 6% (n = 73) Other/Multiracial. In adjusted analyses, statistically more severe EASI lichenification was noted among Black compared with White patients at the head and neck (mean difference, 0.21, [95% CI 0.06, 0.36]; p = 0.01), trunk (0.32, [0.17, 0.47]; p < 0.001), upper extremities (0.27, [0.09, 0.44]; p = 0.008), and lower extremities (0.39, [0.21, 0.57]; p < 0.001). Statistically more severe EASI lichenification was observed among Asian vs White patients in certain areas (mean difference, head and neck, 0.22 [0.04, 0.39], p = 0.01; trunk, 0.25 [0.07, 0.43], p < 0.001; lower extremities, 0.22 [0.01, 0.43], p < 0.001) and SCORing for AD lichenification (mean difference: 0.34 [0.15, 0.52]; p < 0.001). Significantly higher mean pruritus over the past 7 days for Black (mean difference: 0.63 [0.01, 1.26] and Hispanic patients (0.60 [0.11, 1.09]; p = 0.03) vs White patients was observed. Among AD clinical features, the prevalence of facial erythema was significantly lower among Black compared with White patients (prevalence ratio = 0.38, [0.22, 0.67]; p = 0.007). CONCLUSION: Racial/ethnic differences exist in sociodemographic, clinical and treatment characteristics, disease severity, and PROs among real-world AD patients who are candidates for systemic therapy. Recognizing these variations may be of critical importance for dermatologists for the design and delivery of targeted/personalized medicine approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".