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Application of least absolute shrinkage and selection operator logistic regression for the histopathological comparison of chondrodermatitis nodularis helicis and hyperplastic actinic keratosis.
Narala, Saisindhu; Li, Shirley Q; Klimas, Natasha K; Patel, Anisha B.
Affiliation
  • Narala S; Department of Dermatology, University of Texas Medical School at Houston, Houston, Texas, USA.
  • Li SQ; Baylor College of Medicine, Houston, Texas, USA.
  • Klimas NK; Department of Dermatology, University of Texas Medical School at Houston, Houston, Texas, USA.
  • Patel AB; Department of Dermatology, University of Texas Medical School at Houston, Houston, Texas, USA.
J Cutan Pathol ; 48(6): 739-744, 2021 Jun.
Article in En | MEDLINE | ID: mdl-33617003
ABSTRACT

BACKGROUND:

The distinction between chondrodermatitis nodularis helicis (CNH) and hyperplastic actinic keratosis (HAK) on the ear can pose a diagnostic challenge. We aimed to identify histopathological characteristics that could distinguish between CNH and HAK on routine sections using penalized least absolute shrinkage and selection operator (LASSO) logistic regression analysis.

METHODS:

Cases of CNH (n = 80) and HAK (n = 28) were analyzed for selected histopathological characteristics. Fisher's exact test and LASSO regression were performed.

RESULTS:

In univariate analyses, the following were significantly associated with CNH ulceration, acanthosis, granular layer in the majority of the lesion, hypergranulosis at the periphery of the lesion, hyperkeratosis at the periphery of the lesion, hyperparakeratosis at the periphery of the lesion, fibrosis, increased blood vessels, vertically oriented blood vessels, and fibrin. A LASSO model excluding atypia found that fibrin, fibrosis, presence of granular layer, ulceration, and vertically oriented blood vessels were most predictive of CNH. Keratinized strap cells were not a significant predictor.

CONCLUSION:

We have identified features that may aid in differentiating these entities and demonstrated that a LASSO regression model can identify predictors that may improve diagnostic accuracy. Our results indicate that the highest diagnostic accuracy in this dilemma is dependent on obtaining biopsy specimens with visible dermis.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cartilage Diseases / Dermatitis / Keratosis, Actinic / Hyperplasia Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: J Cutan Pathol Year: 2021 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cartilage Diseases / Dermatitis / Keratosis, Actinic / Hyperplasia Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: J Cutan Pathol Year: 2021 Type: Article Affiliation country: United States