Evidence map›Paper›PMID 36344635›Full record

ArticleJournal of digital imaging2023

Non-Expert Markings of Active Chronic Graft-Versus-Host Disease Photographs: Optimal Metrics of Training Effects.

Kelsey Parks, Xiaoqi Liu, Tahsin Reasat, Zain Khera, Laura X Baker, Heidi Chen, Benoit M Dawant, Inga Saknite, Eric R Tkaczyk

Open access · greenAbstract read
In one paragraph

Article in Journal of digital imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 40% of its field
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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Guideline
  2. Review
  3. Article
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

9 authors at 3 institutions in 2 countries.

Kelsey ParksDermatology Service and Research Service, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN, USA.ORCID 0000-0002-0331-3884
Xiaoqi LiuDermatology Service and Research Service, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN, USA.ORCID 0000-0001-5959-5166
Tahsin ReasatDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.ORCID 0000-0001-9451-6814
Zain KheraDermatology Service and Research Service, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN, USA.
Laura X BakerDermatology Service and Research Service, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN, USA.ORCID 0000-0002-0655-0164
Heidi ChenDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0001-5668-2758
Benoit M DawantDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.ORCID 0000-0002-3804-8400
Inga SakniteDepartment of Dermatology, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0002-4000-5485
Eric R TkaczykDermatology Service and Research Service, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN, USA. eric.tkaczyk@vumc.org.ORCID 0000-0002-2850-4740
Vanderbilt University · USVA Tennessee Valley Healthcare System · USVanderbilt University Medical Center · US

Funding

Vanderbilt Clinical Oncology Research Career Development ProgramK12CA090625 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Debra L. Friedman, Paula Jill Hurley · 2001 to 2026
$16.9M
Automatic analysis of 3D skin images for chronic graft-versus-host disease (cGVHD) severity assessmentR21AR074589 · NIAMS · VANDERBILT UNIVERSITY · PI DAWANT, BENOIT M. · 2019 to 2020
$381k
GVHD quantitative assessment in skin of Veterans post-HCTIK2CX001785 · VA · VETERANS HEALTH ADMINISTRATION · PI TKACZYK, ERIC R · 2019 to 2024
–
CSRD VA IK2 CX001785NCI NIH HHS K12 CA090625NIAMS NIH HHS R21 AR074589
6 · The paper itself

Abstract

Lack of reliable measures of cutaneous chronic graft-versus-host disease (cGVHD) remains a significant challenge. Non-expert assistance in marking photographs of active disease could aid the development of automated segmentation algorithms, but validated metrics to evaluate training effects are lacking. We studied absolute and relative error of marked body surface area (BSA), redness, and the Dice index as potential metrics of non-expert improvement. Three non-experts underwent an extensive training program led by a board-certified dermatologist to mark cGVHD in photographs. At the end of the 4-month training, the dermatologist confirmed that each trainee had learned to accurately mark cGVHD. The trainees' inter- and intra-rater intraclass correlation coefficient estimates were "substantial" to "almost perfect" for both BSA and total redness. For fifteen 3D photos of patients with cGVHD, the trainees' median absolute (relative) BSA error compared to expert marking dropped from 20 cm

Indexed as

Bronchiolitis Obliterans SyndromeGraft vs Host DiseaseAlgorithmsChronic DiseaseHumansSkinBody surface areaDice indexErrorErythemaImage annotationSkin imaging

Identifiers

PMID36344635
PMCPMC9984572
OpenAlexW4308404169

What OpenQuestion holds

Textmetadata
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.