Comparison of methods for characterizing skin pigment diversity in research cohorts
Lipnick, M. S.; Chen, D.; Law, T.; Moore, K.; Lester, J.; Monk, E.; Hendrickson, C. M.; Chou, Y.; Hughes, C.; Behnke, E.; Elmankabadi, S.; Ortiz, L.; Negussie, F.; Leeb, G.; Ehie, O.; Auchus, I.; Igaga, E. N.; Bisegerwa, R.; Okunlola, O.; Bickler, P.; Feiner, J.; Shmuylovich, L.
Show abstract
BackgroundSome pulse oximeters perform worse in people with darker skin, and this may be due to inadequate diversity of skin pigment in device development study cohorts. Guidance is needed to accurately and equitably characterize skin pigment to ensure diversity in research cohorts. We tested multiple methods for characterizing skin pigment to assess comparability and impact on cohort diversity. ObjectivesO_LIAssess reliability and comparability of common skin pigment measurement methods C_LIO_LICompare findings from different anatomical sites C_LIO_LIDemonstrate that pigment cannot be assumed from US National Institutes for Health (NIH) race categories C_LI MethodsWe used three subjective methods (perceived Fitzpatrick pFP, Monk Skin Tone MST and Von Luschan VL) and two objective methods (Konica Minolta CM-700d spectrophotometer and Delfin Skin Color Catch DSCC colorimeter) for individual typology angle (ITA), across multiple measurement sites in adults. We calculated {Delta}E to estimate operator perceptibility thresholds for subjective methods and to determine reproducibility for objective methods. We used each method to categorize participants as light, medium, or dark and compared the impact of method selection on cohort diversity. ResultsWe studied 789 participants, with 33,856 assessments. The MST had the widest luminosity range, and VL had the least discernible adjacent categories. With dark defined as ITA <-30{degrees}, 14% of participants were categorized dark as compared to 26% by pFP or 16% by MST. Approximately half of the dark cohort had an ITA <-50{degrees}. With an ITA threshold <-50{degrees}, only 7% of the cohort was categorized as dark. When Black or African American self-identification was used to define dark, 23% of the cohort was categorized as such. Each self-assigned NIH race category included a wide range of ITA and subjective scale categories. Both ITA and L* from the KM-700d and DSCC demonstrated strong correlation ( > 0.7). ConclusionCommon methods for skin pigment characterization, especially the use of race or subjective scales, have significant limitations. When applied to the same cohort, different methods yield significantly different results, and some may overestimate diversity. Previously published ITA thresholds for defining dark skin are too light and lead to underrepresentation of people with darker skin.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Reconstructed human pigmented skin/epidermis models achieve epidermal pigmentation through melanocore transfer. 90%
- CPT1B-Mediated Fatty Acid Oxidation Induces Pigmentation in Solar Lentigo 89%
- Melanocortin-1 receptor (MC1R) genotypes do not correlate with size in two cohorts of medium-to-giant congenital melanocytic nevi 89%
Similar papers in this journal
- Inflammaging in human photoexposed skin: Early onset of senescence and imbalanced epidermal homeostasis across the decades. 90%
- The vitamin A ester retinyl propionate has a unique metabolic profile and higher retinoid-related bioactivity over retinol and retinyl palmitate in human skin models. 90%
- Fingerprinting of skin cells by live cell Raman spectroscopy reveals melanoma cell heterogeneity and cell-type specific responses to UVR 90%
Similar papers in this journal
Similar papers in this journal
- Predicting skin cancer risk from facial images with an explainable artificial intelligence (XAI) based approach: a proof-of-concept study 91%
- Determining the Impact of Ethnicity on the Accuracy of Measurements of Oxygen Saturations. A Retrospective Cohort Study 89%
- Characterizing Long COVID in an International Cohort: 7 Months of Symptoms and Their Impact 86%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.