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Record W2920674058 · doi:10.1111/bjd.17853

Different definitions of atopic dermatitis: impact on prevalence estimates and associated risk factors

2019· review· en· W2920674058 on OpenAlexaff
Toshinori Nakamura, Sadia Haider, Silvia Colicino, Clare Murray, John W. Holloway, Angela Simpson, Paul Cullinan, Adnan Čustović

Bibliographic record

VenueBritish Journal of Dermatology · 2019
Typereview
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsInstitute of Infection and Immunity
FundersMedical Research Council
KeywordsAtopic dermatitisMedicineEnvironmental healthDermatology

Abstract

fetched live from OpenAlex

BACKGROUND: There is no objective test that can unequivocally confirm the diagnosis of atopic dermatitis (AD), and no uniform clinical definition. OBJECTIVES: To investigate to what extent operational definitions of AD cause fluctuation in the prevalence estimates and the associated risk factors. METHODS: We first reviewed the 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 mutations) among children aged 5 years in two population-based birth cohorts: the 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 four common 'case' definitions and two definitions of 'controls'. The prevalence estimates using different case definitions ranged between 22% and 33% in MAAS, and between 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 filaggrin mutations varied, with odds ratios (95% confidence intervals) ranging from 1·8 (1·1-2·9) to 2·2 (1·3-3·7) in MAAS and 1·7 (0·8-3·7) to 2·3 (1·2-4·5) in Ashford. Associations with filaggrin mutations also differed when using the same 'case' definition but different definitions of 'controls'. CONCLUSIONS: Use of different definitions of AD results in substantial differences in prevalence estimates, the performance of prediction models and association with risk factors. What's already known about this topic? There is no objective test that can unequivocally confirm the diagnosis of atopic dermatitis (AD) and no uniform clinical definition. This results in different definitions utilized in AD studies, raising concerns on the generalizability of the results and comparability across different studies. What does this study add? This study has shown that different definitions of 'cases' and 'controls' have major impacts upon prevalence estimates and associations with risk factors, including genetics, in two population-based birth cohorts. These findings suggest the importance of developing a consensus on AD definitions of both 'controls' and 'cases' to minimize biases in studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.293
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.331
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2019
Admission routes1
Has abstractyes

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