Modelling trajectories of parentally reported and physician‐confirmed atopic dermatitis in a birth cohort study. (22nd November 2021)
- Record Type:
- Journal Article
- Title:
- Modelling trajectories of parentally reported and physician‐confirmed atopic dermatitis in a birth cohort study. (22nd November 2021)
- Main Title:
- Modelling trajectories of parentally reported and physician‐confirmed atopic dermatitis in a birth cohort study
- Authors:
- Nakamura, T.
Haider, S.
Fontanella, S.
Murray, C.S.
Simpson, A.
Custovic, A. - Abstract:
- Summary: Background: In a population‐based birth cohort, we aimed to identify longitudinal trajectories of atopic dermatitis (AD) during childhood using data from different sources (validated questionnaires and healthcare records). We investigated the impact of different AD definitions on such trajectories and their relationships with various risk factors. Methods: Of the 1184 children born into the study, 1083 had information on current AD for at least three follow‐ups from birth to age 11 years and were included in the analysis for parentally reported AD (PRAD). Data were transcribed from healthcare records for 916 of 1184 children for the analysis of doctor‐diagnosed AD (DDAD). We also derived a composite definition of AD (CDAD) (at least two of the following: PRAD, DDAD, current use of AD treatment). Using latent class analysis (LCA), we determined longitudinal profiles of AD using the three definitions. Filaggrin ( FLG ) genotype data were available for 803 white participants. Results: For PRAD, LCA identified four AD classes ('no AD', 'persistent', 'early‐onset remitting' and 'late‐onset'). For DDAD and CDAD, the optimal number of phenotypes was three ('no AD', 'persistent' and 'early‐onset remitting'). Although AD classes at population level appeared similar in different models, a considerable proportion of children ( n = 485, 45%) moved between classes. The association with FLG genotype, atopic diseases and early‐life risk factors was inconsistent across differentSummary: Background: In a population‐based birth cohort, we aimed to identify longitudinal trajectories of atopic dermatitis (AD) during childhood using data from different sources (validated questionnaires and healthcare records). We investigated the impact of different AD definitions on such trajectories and their relationships with various risk factors. Methods: Of the 1184 children born into the study, 1083 had information on current AD for at least three follow‐ups from birth to age 11 years and were included in the analysis for parentally reported AD (PRAD). Data were transcribed from healthcare records for 916 of 1184 children for the analysis of doctor‐diagnosed AD (DDAD). We also derived a composite definition of AD (CDAD) (at least two of the following: PRAD, DDAD, current use of AD treatment). Using latent class analysis (LCA), we determined longitudinal profiles of AD using the three definitions. Filaggrin ( FLG ) genotype data were available for 803 white participants. Results: For PRAD, LCA identified four AD classes ('no AD', 'persistent', 'early‐onset remitting' and 'late‐onset'). For DDAD and CDAD, the optimal number of phenotypes was three ('no AD', 'persistent' and 'early‐onset remitting'). Although AD classes at population level appeared similar in different models, a considerable proportion of children ( n = 485, 45%) moved between classes. The association with FLG genotype, atopic diseases and early‐life risk factors was inconsistent across different definitions, but the association with oral food challenge‐confirmed peanut allergy was similar, with a nine‐ to 11‐fold increase among children in the persistent AD class. In a CDAD model, compared with the early‐onset remitting class, those with persistent AD were significantly more likely to have (at age 3 years) moderate/severe AD, polysensitization and current wheeze, and were less likely to have been breastfed. Conclusions: Standardized composite definitions of AD may help to define AD cases with more precision and identify more consistent long‐term trajectories. Abstract : What is already known about this topic? Atopic dermatitis (AD) is heterogeneous, but there is no general consensus on what the different subtypes are. Techniques such as latent class analysis (LCA) have been used to disentangle the long‐term course of AD. AD phenotypes assigned the same name in different studies often differ in the age of onset, temporal trajectory, distributions within a population and associated risk factors, which makes comparisons difficult and clinical application uncertain. What does this study add? We report that the use of different data sources and definitions of AD has a major influence on the number and type of AD phenotypes identified by longitudinal LCA, in addition to the phenotype membership among individual children. Although AD latent classes, at a population level, appeared similar when different definitions were used, almost half of the children changed class allocation in different models. The association with oral food challenge‐confirmed peanut allergy across all models was similar, with a striking nine‐ to 11‐fold increase among children in the persistent AD class. Linked Comment: S-P. Sinikumpu and L. Huilaja. Br J Dermatol 2022; 186:208–209 . Plain language summary available online … (more)
- Is Part Of:
- British journal of dermatology. Volume 186:Number 2(2022)
- Journal:
- British journal of dermatology
- Issue:
- Volume 186:Number 2(2022)
- Issue Display:
- Volume 186, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 186
- Issue:
- 2
- Issue Sort Value:
- 2022-0186-0002-0000
- Page Start:
- 274
- Page End:
- 284
- Publication Date:
- 2021-11-22
- Subjects:
- Dermatology -- Periodicals
Skin -- Diseases -- Periodicals
616.5 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2133 ↗
https://academic.oup.com/bjd ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/bjd.20767 ↗
- Languages:
- English
- ISSNs:
- 0007-0963
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2307.400000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 27133.xml