DERMACLEAR: AI‐Powered Insights Into Four Chronic Inflammatory Skin Diseases in Spain

ABSTRACT Background Hidradenitis suppurativa (HS), chronic urticaria (CU), psoriasis (PsO) and atopic dermatitis (AD) are chronic inflammatory skin diseases associated with substantial morbidity and that compromise quality of life. Enhancing understanding of their prevalence, clinical characteristics, treatment patterns and outcomes is crucial for improving early diagnosis and effective care. Objectives To provide an overview of the proportion and characteristics of patients with HS, CU, PsO and AD by applying artificial intelligence (AI) to real‐world data. Methods DERMACLEAR was a multicenter, national, retrospective study. Electronic health records (EHRs) of patients with the four target diseases and at least one recorded visit at seven centers in Spain between 2016 and 2021 were processed using an AI‐based system incorporating machine learning and natural language processing (NLP). Disease relative frequency, patients' demographic and clinical characteristics and associated healthcare burden were assessed. Results Among 49,779 patients identified with only one of the studied diseases, 8.3% ( n = 4124) had HS, 13.4% ( n = 6660) CU, 58.8% ( n = 29,262) PsO and 19.6% ( n = 9733) AD. The mean age was 52.9 years (range: 18–105), and 56.5% were women. According to data retrieved by the AI system from EHRs of 434 patients, the mean body mass index was 29.0 kg/m 2 . Overall, a high prevalence of concomitant conditions was observed, with infections/infestations recorded in 68.7% of patients and respiratory disorders in 59.1% at any time during the study period. The annualized mean of dermatology visits was 26,843.2, 7,154.7, 5,063.1 and 3,272.9 in patients with PsO, AD, CU and HS, respectively. At the database closure, 5580 (11.2%) patients were recorded as deceased during the study period. Conclusions Applying AI and NLP to real‐world clinical data offers valuable insights into the characteristics and healthcare impact of HS, CU, PsO and AD. Our findings support the need for more personalized treatments and integrated follow‐up, addressing both the primary disease and associated comorbidities.

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Journal
JEADV Clinical Practice
Published
2026-04-20
DOI
https://doi.org/10.1002/jvc2.70339
Primary Topic
Hidradenitis Suppurativa and Treatments
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article
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article

DERMACLEAR: AI‐Powered Insights Into Four Chronic Inflammatory Skin Diseases in Spain

José Ignacio Rojo-Laguna, A. Martín‐Santiago, E. Daudén, Lluis Puig et al.
JEADV Clinical Practice
Hidradenitis Suppurativa and Treatments
article

DERMACLEAR: AI‐Powered Insights Into Four Chronic Inflammatory Skin Diseases in Spain

José Ignacio Rojo-Laguna, A. Martín‐Santiago, E. Daudén, Lluis Puig, Javier Ortiz de Frutos, José Luis López-Estebaranz, Raquel Rivera‐Díaz, Elisabet Fernández‐Martínez, Jaume Notario Rosa, Vicente García‐Patos Briones, Lara Gómez‐Labrador
article en

Abstract

ABSTRACT Background Hidradenitis suppurativa (HS), chronic urticaria (CU), psoriasis (PsO) and atopic dermatitis (AD) are chronic inflammatory skin diseases associated with substantial morbidity and that compromise quality of life. Enhancing understanding of their prevalence, clinical characteristics, treatment patterns and outcomes is crucial for improving early diagnosis and effective care. Objectives To provide an overview of the proportion and characteristics of patients with HS, CU, PsO and AD by applying artificial intelligence (AI) to real‐world data. Methods DERMACLEAR was a multicenter, national, retrospective study. Electronic health records (EHRs) of patients with the four target diseases and at least one recorded visit at seven centers in Spain between 2016 and 2021 were processed using an AI‐based system incorporating machine learning and natural language processing (NLP). Disease relative frequency, patients' demographic and clinical characteristics and associated healthcare burden were assessed. Results Among 49,779 patients identified with only one of the studied diseases, 8.3% ( n = 4124) had HS, 13.4% ( n = 6660) CU, 58.8% ( n = 29,262) PsO and 19.6% ( n = 9733) AD. The mean age was 52.9 years (range: 18–105), and 56.5% were women. According to data retrieved by the AI system from EHRs of 434 patients, the mean body mass index was 29.0 kg/m 2 . Overall, a high prevalence of concomitant conditions was observed, with infections/infestations recorded in 68.7% of patients and respiratory disorders in 59.1% at any time during the study period. The annualized mean of dermatology visits was 26,843.2, 7,154.7, 5,063.1 and 3,272.9 in patients with PsO, AD, CU and HS, respectively. At the database closure, 5580 (11.2%) patients were recorded as deceased during the study period. Conclusions Applying AI and NLP to real‐world clinical data offers valuable insights into the characteristics and healthcare impact of HS, CU, PsO and AD. Our findings support the need for more personalized treatments and integrated follow‐up, addressing both the primary disease and associated comorbidities.

JEADV Clinical Practice
Hospital de Sant Pau (ES), Bellvitge University Hospital (ES), Hospital Universitario Fundación Alcorcón (ES), Hospital Universitario 12 De Octubre (ES), Vall d'Hebron Hospital Universitari (ES), Hospital Universitario de La Princesa (ES), Hospital Del Mar (ES), Novartis (Spain) (ES), Hospital Universitario Son Espases (ES)
Quality Education
Openalex Percentile: Top 10%
Hidradenitis Suppurativa and Treatments
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