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| 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) |
| Appears in Collections: | Artículos |
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