Evidence map›Paper›PMID 39014060›Full record

ReviewNPJ digital medicine2024

A survey of skin tone assessment in prospective research.

Vanessa R Weir, Katelyn Dempsey, Judy Wawira Gichoya, Veronica Rotemberg, An-Kwok Ian Wong

Abstract readReview
In one paragraph

Review in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  10. Photochemical synergy in hybrid sunscreen gels: enhanced UV protection and photostability with algal antioxidants, quercetin, azobenzene, and chitosan-coated TiO₂ nanoparticles.Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology · 2026
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  13. Observational
  14. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Vanessa R Weir *Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID http://orcid.org/0000-0002-7338-4784
Katelyn Dempsey *Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University, Durham, NC, USA.
Judy Wawira GichoyaDepartment of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA.ORCID http://orcid.org/0000-0002-1097-316X
Veronica RotembergDermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA. rotembev@mskcc.org.
An-Kwok Ian WongDepartment of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University, Durham, NC, USA. a.ian.wong@duke.edu.ORCID http://orcid.org/0000-0001-5668-4251

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Support for QA/QC for Prior Approval ProcessUL1TR002553 · NCATS · DUKE UNIVERSITY · PI LI, JENNIFER S, MCNAMARA, JAMES O. · 2018 to 2023
$58.5M
Research Project 3U54MD012530 · NIMHD · DUKE UNIVERSITY · PI JOHNSON, KIMBERLY S. · 2017 to 2022
$8.8M
RADX TECH - CERES NANOSCIENCE INC NANOTRAP PARTICLE MANUFACTURING75N92020C00021 · NHLBI · CERES NANOSCIENCES, LLLP · PI DUNLAP, ROSS · 2021 to 2021
$4.0M
Opportunistic Screening for ASCVD using a Multimodal Deep Learning Risk Prediction ModelR01HL167811 · NHLBI · MAYO CLINIC ARIZONA · PI Imon Banerjee, Judy Gichoya · 2024 to 2026
$2.1M
NCATS NIH HHS UL1 TR002553NCI NIH HHS P30 CA008748NHLBI NIH HHS 75N92020C00008NHLBI NIH HHS 75N92020C00021NHLBI NIH HHS R01 HL167811NIMHD NIH HHS U54 MD012530U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS) UL1TR002553U.S. Department of Health & Human Services | NIH | National Institute on Minority Health and Health Disparities (NIMHD) U54MD012530
6 · The paper itself

Abstract

Increasing evidence supports reduced accuracy of noninvasive assessment tools, such as pulse oximetry, temperature probes, and AI skin diagnosis benchmarks, in patients with darker skin tones. The FDA is exploring potential strategies for device regulation to improve performance across diverse skin tones by including skin tone criteria. However, there is no consensus about how prospective studies should perform skin tone assessment in order to take this bias into account. There are several tools available to conduct skin tone assessments including administered visual scales (e.g., Fitzpatrick Skin Type, Pantone, Monk Skin Tone) and color measurement tools (e.g., reflectance colorimeters, reflectance spectrophotometers, cameras), although none are consistently used or validated across multiple medical domains. Accurate and consistent skin tone measurement depends on many factors including standardized environments, lighting, body parts assessed, patient conditions, and choice of skin tone assessment tool(s). As race and ethnicity are inadequate proxies for skin tone, these considerations can be helpful in standardizing the effect of skin tone on studies such as AI dermatology diagnoses, pulse oximetry, and temporal thermometers. Skin tone bias in medical devices is likely due to systemic factors that lead to inadequate validation across diverse skin tones. There is an opportunity for researchers to use skin tone assessment methods with standardized considerations in prospective studies of noninvasive tools that may be affected by skin tone. We propose considerations that researchers must take in order to improve device robustness to skin tone bias.

Identifiers

PMID39014060
PMCPMC11252344

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.