JAMA Dermatology

<jats:sec id="ab-doi250033-4"><jats:title>Importance</jats:title><jats:p>The disease course of atopic dermatitis (AD) is characterized by fluctuations and frequent flares, contributing to the disease burden and impairment in life quality. However, flares are not necessarily considered in severity classifications and clinical treatment decisions.</jats:p></jats:sec><jats:sec id="ab-doi250033-5"><jats:title>Objective</jats:title><jats:p>To validate the predictability of flares and disease severity in patients with AD and quantify the importance of predictors.</jats:p></jats:sec><jats:sec id="ab-doi250033-6"><jats:title>Design, Setting, and Participants</jats:title><jats:p>Using the Danish Skin Cohort, a large population of patients with AD from Denmark with data on disease severity and flare patterns, quantile regression models were conducted to investigate the association between the number of flares reported in 2022 and patient-reported severity measures reported in 2023. Additionally, boosted random forests were used to explore predictors of both annual flares and disease severity. Analyses were conducted from January to December of 2024.</jats:p></jats:sec><jats:sec id="ab-doi250033-7"><jats:title>Main Outcomes and Measures</jats:title><jats:p>Severity of AD as well as frequency, duration, and severity of flares were the main variables under consideration.</jats:p></jats:sec><jats:sec id="ab-doi250033-8"><jats:title>Results</jats:title><jats:p>This study included 878 patients with AD (median [IQR] age, 49.0 [39.0-59.0] years), with 26 reporting 0 yearly flares, 405 reporting 1 to 5 yearly flares, 169 reporting 6 to 10 yearly flares, and 278 patients reporting more than 10 yearly flares in 2022. From the quantile regression, the number of annual flares reported in 2022 was significantly associated with most patient-reported severity measures reported in 2023. When adjusting for the Patient-Oriented Scoring of Atopic Dermatitis score at baseline, the number of annual flares reported in 2022 was significantly associated with the Patient-Oriented Eczema Measure and Dermatology Life Quality Index. Using predictive machine learning models, flare severity, duration, and number were among the most important predictors of AD severity, while disease severity was among the strongest predictors of the number of annual flares.</jats:p></jats:sec><jats:sec id="ab-doi250033-9"><jats:title>Conclusions and Relevance</jats:title><jats:p>This cohort study found that a higher number of flares was associated with lower quality of life and was identified as a predictor of more severe AD in the following year. These results highlight the relevance of flares in the assessment of severity or disease prognosis and suggest the need for a threshold for an acceptable number of flares in treatment decisions to achieve better disease control and improved quality of life for patients.</jats:p></jats:sec>

Trends in eczema prevalence in children and adolescents: a Global Asthma Network phase i study.

Clin Exp Allergy

The prevalence of childhood atopic eczema in a general population.

J Am Acad Dermatol

The epidemiology and global burden of atopic dermatitis: a narrative review.

Life (Basel)

Atopic dermatitis and the atopic march.

J Allergy Clin Immunol

Severity scoring of atopic dermatitis: the SCORAD index. Consensus Report of the European Task Force on Atopic Dermatitis.

Dermatology

The eczema area and severity index (EASI): assessment of reliability in atopic dermatitis.

Exp Dermatol

The patient-oriented eczema measure: development and initial validation of a new tool for measuring atopic eczema severity from the patients’ perspective.

Arch Dermatol

Guidelines of care for the management of atopic dermatitis: section 4: prevention of disease flares and use of adjunctive therapies and approaches.

A systematic review and meta-analysis of the regional and age-related differences in atopic dermatitis clinical characteristics.

Atopic dermatitis endotypes and implications for targeted therapeutics.

Once-daily crisaborole ointment, 2%, as a long-term maintenance treatment in patients aged = 3 months with mild-to-moderate atopic dermatitis: a 52-week clinical study.

Am J Clin Dermatol

Extent and consequences of inadequate disease control among adults with a history of moderate to severe atopic dermatitis.

J Dermatol

ETFAD/EADV Eczema task force 2020 position paper on diagnosis and treatment of atopic dermatitis in adults and children.

J Eur Acad Dermatol Venereol

From local explanations to global understanding with explainable AI for trees.

Nat Mach Intell

Dermatology Life Quality Index (DLQI): a simple practical measure for routine clinical use.

Clin Exp Dermatol

Atopic dermatitis phenotypes based on cluster analysis of the Danish Skin Cohort.

Br J Dermatol

Characterization of patients with atopic dermatitis based on flare patterns and severity of disease: a Danish population-based study.

Factors predicting quality of life impairment in adult patients with atopic dermatitis: results from a patient survey and machine learning analysis.

Dermatol Ther (Heidelb)

Longitudinal course and predictors of depressive symptoms in atopic dermatitis.

Personalized prediction of daily eczema severity scores using a mechanistic machine learning model.

Impact of environmental factors in predicting daily severity scores of atopic dermatitis.

Clin Transl Allergy

The disease course of atopic dermatitis (AD) is characterized by fluctuations and frequent flares, contributing to the disease burden and impairment in life quality. However, flares are not necessarily considered in severity classifications and clinical treatment decisions.
To validate the predictability of flares and disease severity in patients with AD and quantify the importance of predictors.
Using the Danish Skin Cohort, a large population of patients with AD from Denmark with data on disease severity and flare patterns, quantile regression models were conducted to investigate the association between the number of flares reported in 2022 and patient-reported severity measures reported in 2023. Additionally, boosted random forests were used to explore predictors of both annual flares and disease severity. Analyses were conducted from January to December of 2024.
Severity of AD as well as frequency, duration, and severity of flares were the main variables under consideration.
This study included 878 patients with AD (median [IQR] age, 49.0 [39.0-59.0] years), with 26 reporting 0 yearly flares, 405 reporting 1 to 5 yearly flares, 169 reporting 6 to 10 yearly flares, and 278 patients reporting more than 10 yearly flares in 2022. From the quantile regression, the number of annual flares reported in 2022 was significantly associated with most patient-reported severity measures reported in 2023. When adjusting for the Patient-Oriented Scoring of Atopic Dermatitis score at baseline, the number of annual flares reported in 2022 was significantly associated with the Patient-Oriented Eczema Measure and Dermatology Life Quality Index. Using predictive machine learning models, flare severity, duration, and number were among the most important predictors of AD severity, while disease severity was among the strongest predictors of the number of annual flares.
This cohort study found that a higher number of flares was associated with lower quality of life and was identified as a predictor of more severe AD in the following year. These results highlight the relevance of flares in the assessment of severity or disease prognosis and suggest the need for a threshold for an acceptable number of flares in treatment decisions to achieve better disease control and improved quality of life for patients.

Predictors of Flares and Disease Severity in Patients With Atopic Dermatitis Using Machine Learning.

Predictors of Flares and Disease Severity in Patients With Atopic Dermatitis Using Machine Learning

Predictors of Flares and Disease Severity in Patients With Atopic Dermatitis Using Machine Learning

Clinical Summary

What was studied

Key findings

Clinical implications

Related Questions