Please use this identifier to cite or link to this item: https://accedacris.ulpgc.es/jspui/handle/10553/159588
Title: Clinical Factors Associated With Current Relevance in Allergic Contact Dermatitis: Development of Predictive Models Based on Data From the Spanish Contact Dermatitis Register (REIDAC)
Authors: Pesqué, David
Ortiz de Frutos, Francisco Javier
Navarro-Triviño, Francisco
Sanz-Sánchez, Tatiana
Zaragoza-Ninet, Violeta
Córdoba-Guijarro, Susana
Miquel-Miquel, Javier
Silvestre-Salvador, Juan Francisco
González-Pérez, Ricardo
Ruiz-González, Inmaculada
Mercader-García, Pedro
Serra-Baldrich, Esther
Carrascosa-Carrillo, José Manuel
Tous-Romero, Fátima
Rodríguez-Serna, Mercedes
Gatica-Ortega, María Elena
Paredes-Suárez, Carmen
Pastor-Nieto, María Antonia
Chicharro, Pablo
Andreu, Marta
Sánchez-Gilo, Araceli
Pereyra-Rodríguez, José Juan
Melé-Ninot, Gemma
Sánchez-Pedreño Guillén, Paloma
Gómez de la Fuente, Enrique
Elosua-González, Marta
Gallardo, Fernando
Pujol, Ramon M.
García-Doval, Ignacio
Borrego Hernando, Leopoldo 
Descalzo, Miguel Ángel
Giménez-Arnau, Ana M.
UNESCO Clasification: 32 Ciencias médicas
320106 Dermatología
320701 Alergias
Keywords: Contact Dermatitis
Machine Learning
Model
Patch Test
Predictive, et al
Issue Date: 2026
Journal: Contact Dermatitis 
Abstract: Background: Current relevance of positive patch-test reactions guides management in allergic contact dermatitis (ACD), yet its clinical predictors and the use of predictive models in clinical practice remain underused. Objectives: To identify demographic and clinical factors associated with current relevance in ACD and to develop overall and allergen-specific predictive models. Methods: A multicentric REIDAC study included data from patch-tested patients with the Spanish baseline series. Exposure history, anatomical sites, atopic status, and occupational data were recorded. Logistic regression (LR) models were trained and internally validated to predict current relevance overall and for top frequent allergens. Model discrimination was assessed with area under the receiver-operating characteristic curve (AUC). Results: Among 17 005 patients, 4077 (24.0%) had at least one currently relevant reaction. The final overall LR model achieved an AUC for the validation sample of 0.679. Allergen-specific AUC parameters (LR) varied among allergens but performed best for nickel (AUC = 0.770). The independent factors associated with current relevance were female gender, specific body sites (hand, neck, head, leg, feet) and two occupations (hairdresser and construction workers). The use of other models (LASSO, gradient boosting) revealed similar results. Conclusions: Prediction modelling may moderately predict current relevance in ACD and several clinical variables are associated with current relevance in ACD.
URI: https://accedacris.ulpgc.es/jspui/handle/10553/159588
ISSN: 0105-1873
DOI: 10.1111/cod.70089
Source: Contact Dermatitis [ISSN 0105-1873], (Febrero 2026)
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