Evidence map›Paper›PMID 42581451›Full record

ArticleThe Journal of dermatology2026

A Prediction Model for the Differential Diagnosis of Bowen's Disease and Bowenoid Actinic Keratosis.

Byeonghyun Joo, Hyungrye Noh, Jin Ho Kim, Jong Hee Lee, Dongyoun Lee, Jun Young Kim, Jihye Park

Abstract read
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Article in The Journal of dermatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Byeonghyun JooDepartment of Dermatology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0007-5045-5619
Hyungrye NohDepartment of Dermatology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-7871-8782
Jin Ho KimDepartment of Dermatology, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea.ORCID https://orcid.org/0000-0003-4315-8134
Jong Hee LeeDepartment of Dermatology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-8536-1179
Dongyoun LeeDepartment of Dermatology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-0765-9812
Jun Young KimDepartment of Dermatology, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea.ORCID https://orcid.org/0000-0002-2999-1018
Jihye ParkDepartment of Dermatology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-6699-5202

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bowen's disease and bowenoid actinic keratosis share overlapping clinical and histopathological features, and there is no clear consensus regarding their differential diagnosis. This study aimed to identify clinicopathological differences between the two diseases and to develop a diagnostic prediction model in a Korean population. We retrospectively analyzed 253 patients pathologically diagnosed with Bowen's disease or bowenoid actinic keratosis at a single institution in South Korea. Clinical and histopathological variables were compared between the two groups, and significant variables were incorporated into a multivariable logistic regression model. The model was externally validated using an independent cohort of 207 patients from another institution in South Korea. In the development cohort, variables significantly associated with diagnosis included lesion location, adjacent pigmented lesions, solar elastosis, pathologically identical lesions in the same region, and the number of atypical cells within a 3 mm width of the epidermis. The prediction model showed good discriminative performance, with an area under the receiver operating characteristic curve of 0.897. In the external validation cohort, the model demonstrated excellent performance, with an area under the curve of 0.994 and an accuracy of 95.17%. These findings suggest that integration of clinical and histopathological features may help differentiate Bowen's disease from bowenoid actinic keratosis in Korean clinical settings. Further validation in ethnically and geographically diverse populations is needed before broader application of the proposed model.

Indexed as

Bowen's DiseaseKeratosis, ActinicSkin NeoplasmsAgedAged, 80 and overDiagnosis, DifferentialFemaleHumansLogistic ModelsMaleMiddle AgedNon-Melanoma Skin NeoplasmsRepublic of KoreaRetrospective Studiesactinic keratosisBowen's diseasediagnosisdifferentialkeratinocytesprediction model

Identifiers

PMID42581451
PMCPMC13646856

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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.