Abstract
Background
There is no objective test that can unequivocally confirm the diagnosis of atopic dermatitis (AD), and no uniform clinical definition.
Objective
To investigate to what extent operational definitions of AD cause fluctuation in the prevalence estimates and the associated risk factors.
Methods
We first reviewed operational definitions of AD used in the literature. We then tested the impact of the choice of the most common definitions of “Cases” and “Controls” on AD prevalence estimates and associated risk factors (including filaggrin‐FLG mutations) among children aged 5 years in two population‐based birth cohorts: Manchester Asthma and Allergy Study (MAAS) and Asthma in Ashford. Model performance was measured by the percentage of children within an area of clinical indecision (defined as having a posterior probability of AD between 25% and 60%).
Results
We identified 59 different definitions of AD across 45 reviewed studies. Of those, we chose 4 common “Case” definitions, and 2 definitions of “Controls”. The prevalence estimates using different case definitions ranged between 22% and 33% in MAAS, and 12% and 22% in Ashford. The area of clinical indecision ranged from 32% to 44% in MAAS, and from 9% to 29% in Ashford. Depending on the case definition used, the associations with FLG mutations varied (ORs [95% CI]: 1.8 [1.1‐2.9] to 2.2 [1.3‐3.7] (MAAS) and 1.7 [0.8‐3.7] to 2.3 [1.2‐4.5] (Ashford)). Associations with FLG mutations also differed when using the same “Case” definition, but different definitions of “Controls”.
Conclusion
Use of different definitions of AD results in substantial difference in prevalence estimates, the performance of prediction models, and association with risk factors.
There is no objective test that can unequivocally confirm the diagnosis of atopic dermatitis (AD), and no uniform clinical definition.
Objective
To investigate to what extent operational definitions of AD cause fluctuation in the prevalence estimates and the associated risk factors.
Methods
We first reviewed operational definitions of AD used in the literature. We then tested the impact of the choice of the most common definitions of “Cases” and “Controls” on AD prevalence estimates and associated risk factors (including filaggrin‐FLG mutations) among children aged 5 years in two population‐based birth cohorts: Manchester Asthma and Allergy Study (MAAS) and Asthma in Ashford. Model performance was measured by the percentage of children within an area of clinical indecision (defined as having a posterior probability of AD between 25% and 60%).
Results
We identified 59 different definitions of AD across 45 reviewed studies. Of those, we chose 4 common “Case” definitions, and 2 definitions of “Controls”. The prevalence estimates using different case definitions ranged between 22% and 33% in MAAS, and 12% and 22% in Ashford. The area of clinical indecision ranged from 32% to 44% in MAAS, and from 9% to 29% in Ashford. Depending on the case definition used, the associations with FLG mutations varied (ORs [95% CI]: 1.8 [1.1‐2.9] to 2.2 [1.3‐3.7] (MAAS) and 1.7 [0.8‐3.7] to 2.3 [1.2‐4.5] (Ashford)). Associations with FLG mutations also differed when using the same “Case” definition, but different definitions of “Controls”.
Conclusion
Use of different definitions of AD results in substantial difference in prevalence estimates, the performance of prediction models, and association with risk factors.
| Original language | English |
|---|---|
| Journal | British Journal of Dermatology |
| Early online date | 1 Mar 2019 |
| DOIs | |
| Publication status | Published - 2019 |
