Disease Trajectories in Childhood Atopic Dermatitis

An Update and Practitioner's Guide

A.D. Irvine; P. Mina-Osorio


The British Journal of Dermatology. 2019;181(5):895-906. 

In This Article

Novel Approaches to Analysing Longitudinal Data Disclose Clear and Reproducible Atopic Dermatitis Phenotypes

In an attempt to address these confounding factors and biases, advanced analytical techniques frequently used in other fields, such as oncology, are being applied in atopic disease to elucidate complex disease phenotypes through pattern identification in large datasets. One example is machine-learning methods, a data-driven approach (not without limitations) that can capture the heterogeneity in longitudinal patterns of disease within individual patients, where conventional methods might overemphasize the prevalence of discrete subsets such as the atopic march phenotype.[41,45,65,66] Latent-class analysis helps to overcome investigator bias when evaluating temporal patterns of age of onset and sensitization, as well as distinguishing overlapping categories of allergen sensitization.[10,44,45]

Interestingly, despite the variety of analytical methods applied, several common themes have emerged from multiple cohorts, suggesting that some of these phenotypes are highly reproducible and are likely to be clinically relevant. Figure 3 lists some of the phenotypes that have been identified using a few large, high-quality studies, and highlights their commonalities. These more recent analyses show that while the atopic march is supported by cross-sectional analyses of longitudinal studies, most atopic individuals do not follow this classical longitudinal pattern, suggesting that multiple trajectories of longitudinal disease progression exist (Figure 4).[19,25,41,42,44,45,67–73]

Figure 3.

Despite the different methodologies used in recent data-driven analyses of cohort data, the characteristics of the patient clusters representing distinct trajectories of disease progression are remarkably similar among studies. We have consolidated the information from the table into four more or less overlapping subsets represented in different shades of red in the concentric circles. AD, atopic dermatitis; ALSPAC, Avon Longitudinal Study of Parents and Children; MAAS, Manchester Asthma and Allergy Study; MAS, Multicenter Allergy Study; MeDALL, Mechanisms of the Development of Allergy; PARIS, Pollution and Asthma Risk: an Infant Study; PASTURE, Protection Against Allergy: Study in Rural Environments; PIAMA, Prevention and Incidence of Asthma and Mite Allergy.

Figure 4.

Paediatric patients with atopic dermatitis (AD) can follow multiple trajectories of disease progression. The atopic march represents one of multiple such possible trajectories. Analysing data cross-sectionally at a population level at any of the indicated time points could result in either under- or overestimation of the co-occurrence of any number of atopic comorbidities studied. The figure is based on the findings described by Belgrave et al.41