The Epidemiology of Atopic Dermatitis, Associated Comorbidities, and Treatment Patterns in the United Kingdom (UK)
Conditions: Atopic Dermatitis Eczema, Atopic Dermatitis, Eczema
Sponsor: Momentum Data

 
 
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Official Title: Trends in the Epidemiology and 
Treatment of Atopic Dermatitis in the United 
Kingdom (UK) 
 
NCT number: NCT03823794  
 
Date: 21 May 2021 
 
 

 
 
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Working Title: The incidence, prevalence, 
treatment patterns, and disease management for 
atopic dermatitis in the UK 
Academic contributors 
Carsten Flohr1, Simon de Lusignan2 
 
1 St John's Institute of Dermatology, Guy's & St Thomas' NHS Foundation Trust and King's College 
London 
2 Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United 
Kingdom 
 
 
 
The research is supported by Momentum Data Ltd 
 
 
 
 
 
 

 
 
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Abstract 
Background 
Atopic dermatitis (AD), also known as atopic eczema, is the most common chronic inflammatory 
skin condition however there are large variations in prevalence estimates. It is also associated 
with other atopic conditions, and mental health conditions although the strength of these 
associations has not been fully explored. It is also not clear how much healthcare resource 
utilisation there is by people with AD in the UK. 
 
Objective 
We aim to calculate current and accurate prevalence and incidence estimates for AD by age 
group and sociodemographic factors. We also aim to describe the burden of comorbidity in AD 
with a focus on atopic and mental health conditions. We also aim to describe the health care 
resource utilisation of this cohort in terms of prescription use, primary care appointments, and 
specialist referrals. 
 
Method 
We will define AD cases using a previously validated algorithm for case identification use clinical 
codes form primary care in the UK (Read codes). We will analyse the population prevalence and 
incidence of AD using this definition over a 10-year period (2008-2018). Within this population 
we will report the prevalence of autoimmune conditions (rheumatoid arthritis, inflammatory 
bowel disease, coeliac disease, type 1 diabetes, and multiple sclerosis) compared with a cohort 
of individuals without a diagnosis of AD, matched by age and sex at GP practice level. In the same 
cohort we will also report the annual use of topical and oral medications used for the treatment 
of AD, primary care appointments, and specialist referrals, overall and stratified by 
sociodemographic factors. 
 
 
 

 
 
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Lay Summary 
Atopic dermatitis, commonly called eczema, is one of the most frequently occurring skin 
conditions. It is estimated to affect around one fifth of children in developed countries and is also 
becoming increasingly common in less developed countries. Exact estimates of how common 
eczema actually is, vary considerably and there has not been an in-depth analysis of the number 
of people with eczema in the UK. It is also unclear which groups of people are most affected and 
which treatment options are being used. 
 
Most people with eczema are managed by their GP with only a few people requiring specialist 
care. GP records therefore provide an excellent opportunity to explore how common eczema is 
and which treatments are being used currently. Through these studies we aim to provide 
accurate estimates of the number of people with current eczema (prevalence), number 
developing new onset eczema (incidence), and the pattern of common comorbidities in people 
with eczema.  We also aim describe current treatment patterns by age groups and other factors. 
We will look back over the last decade to identify how the number of people with eczema and 
treatments changing over time. We will also explore patterns in the people most commonly 
affected and in the treatments used. 
 
 

 
 
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Introduction 
Atopic dermatitis (AD), also known as atopic eczema, is a chronic inflammatory skin condition 
which affects around 200 million people worldwide.1 It most commonly develops in the first 
year of life although the onset can occur at any age.2,3  AD usually often follows a relapsing-
remitting course and remission may require the use of maintenance therapies.4 Whilst the 
majority of affected children will have resolution or improvement by late childhood,2 a 
substantial proportion of people will have ongoing AD into adulthood and flares can occur even 
after long periods of remission.3,5 AD can be extremely disabling and can have a significant 
psychological impact in both children and adults6-8 and it has been estimated that around 30% 
of AD is moderate or severe.9 The current treatment approach involves avoidance of individual 
trigger factors, the application of emollients, and a multistep approach to the use of anti-
inflammatories depending on disease severity.4 
 
In the UK prevalence estimates vary widely, especially in adults. Recent questionnaire-based 
studies suggest wide ranging prevalence rates of 2.5-15%.10,11 Given that 97% of AD patients are 
seen and treated in principally in primary care in the UK, databases of electronic health records 
from GP practices provide a rich data source from which epidemiological analyses can be 
derived.12 Using the UK Clinical Practice Research Datalink (CPRD), approximately 500,000 
people were identified as having AD between 1998-2015 which scales to an approximate UK 
prevalence of 10%.13 However, the limitation of this study is that it was originally designed to 
assess cardiovascular outcomes in AD not prevalence per se and only assessed the adult 
population. Incidence rates of eczema have been recently described in the UK to 2015, but only 
in children.14,15 
 
AD is associated with a wide range of comorbidities. Children with AD are at increased risk of 
asthma and allergic rhinitis,2 and depression is more common in both children and adults.8  
Severe and active AD was also demonstrated to be a risk factor for incident cardiovascular 
disease in a recent UK primary study,13 and an association with an increased risk of new-onset 
rheumatoid arthritis and inflammatory bowel disease, but a decreased risk of type 1 diabetes, 

 
 
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has been observed in population data.16 However, high quality data on the overall pattern of 
comorbidity in individuals with AD are lacking.17  
 
The burden of management falls largely on primary care in the UK with 97% of people with AD 
seen and treated primarily by their GP.12 Attendance rates are also high with 96% children with 
AD reported to have had a primary care attendance within the preceding year.18 It has been 
estimated that 16-30% of AD is moderate or severe,9,18 and whilst those with more severe 
disease are more likely to be referred for specialist care, the majority of these cases are still 
managed without secondary care referral.18 The most significant monetary costs for AD are also 
due to primary care attendances and prescribing.19 Despite this high disease burden of AD a 
contemporary overview of healthcare and treatment utilisation in children and adults with AD 
in the UK is currently lacking. 
 
Aims 
In these retrospective cohort studies, we aim to describe: 
1. The incidence and prevalence of AD in primary care in children and adults, including 
variation by sociodemographic factors and calendar year. 
2. Patterns of possible AD-associated comorbidity post-diagnosis.  
3. Prescribing patterns for individuals with AD, and how prescribing varies by 
sociodemographic factors and calendar time. 
4. Patterns of treatment escalation in individuals with AD.  
Methods 
Study design and population 
We aim to perform a retrospective cohort study using the Royal College of General Practitioners 
Research and Surveillance Centre (RCGP RSC) database. All adults and children of any age 
contributing data to the RCGP RCS database between January 1, 2008 and January 1, 2018 for at 
least one year, will be eligible for inclusion in the study. 
 

 
 
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Treatments for AD are also used to treat other conditions and the indication from treatment is 
not readily available from large datasets in the UK. We will therefore exclude people with 
potential confounding comorbidities from our AD cohort when assessing treatment utilisation. 
We will exclude people with skin conditions also excluded by Abuabara et al.20 (psoriasis, contact 
dermatitis, photodermatitis, and ichthyosis), those with inflammatory bowel disease (IBD), or 
rheumatoid arthritis, and those with a history of organ transplantation. IBD and rheumatoid 
arthritis will be identified using approaches validated in UK primary care databases and 
previously described.21-23 In the absence of a validated method to identify the presence of organ 
transplantation from routine UK primary care data, this will be identified using a Read code list 
generated in accordance with published guidance.24,25 
 
Atopic dermatitis definition 
Individuals with AD will be identified using a validated algorithm developed for use with the UK 
electronic health record,20 and used in recent UK studies in AD.13,14 The positive predictive value 
of this algorithm is 90% (95% Confidence interval (CI) 80-91%) in children and 82% (95% CI 
73- 89%) in adults.20 In brief, AD is identified by the presence of one diagnostic code and with at 
least two eczema-related treatment codes on separate days within three months before or one 
year after the diagnostic code. 
 
AD severity will be defined using the approach used by Silverwood et al. in their study of 
cardiovascular outcomes in AD:13 AD will be considered moderate at the prescription of a second 
potent topical corticosteroid treatment within one year or a first topical calcineurin inhibitor 
(TCI). AD will be considered severe at the first of a systemic immunosuppressant treatment, 
phototherapy, or a dermatology referral. 
 
Active AD has been defined from electronic health records in a recent study as: The onset of 
active AD was defined as the later of two AD records appearing within any one year period.13 
Active AD was then assumed to last for one year, unless another AD record appeared in which 
case its duration was be prolonged for a further one year period.13 We will utilise this approach 

 
 
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but use the first of two codes (rather than the latter) within one year to signify the onset of active 
AD, as this has been shown to have good agreement to physician confirmed onset.20 
 
Primary care visits and specialist referrals definitions 
A primary care visit for AD will be defined as any primary care attendance associated with either 
a diagnostic code for AD or a prescription for one or more AD treatments. Specialist referrals 
will be identified by the presence of a Read code for referral to; a dermatologist, a GP with a 
specialty interest in dermatology, or dermatology specialist nurse. 
 
Definition of baseline variables 
Age will be initially grouped in accordance with trial data reporting, as follows: 0-1, 2-6, 7-11, 
12-17, 18-29, 30-39, 40-49, 50-59, 60-69, 70-79, >80 years. To examine how disease incidence 
varies across other sociodemographic factors stratified by age at diagnosis we will also define 
broader age groups. Ethnicity will be categorised as follows using a previously described 
informatics ontology for ethnicity and using the major UK census categories:26,27 White, Asian, 
Black African/Caribbean, Mixed, Other, or not reported.  
 
Deprivation will be defined based using the official national deprivation measure; index of 
multiple deprivation (IMD).28 IMD is calculated based on patient postcode at the point of data 
extraction. Scores will be divided into quintiles based on the national distribution of IMD scores. 
 
Other factors included for analysis comprise; smoking status, alcohol use, concomitant atopic 
diseases, depression, family history of atopy, biomarkers and laboratory test, and other 
comorbidities. 
 
Definition of atopic dermatitis-associated conditions 
AD-associated conditions considered will comprise: asthma, allergic rhinitis, depression, 
anxiety, other psychological disorders, rheumatoid arthritis, inflammatory bowel disease, 
coeliac disease, type 1 diabetes, multiple sclerosis, and alopecia. 
 

 
 
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Atopic dermatitis treatments 
We will analyse prescription records for the following therapy classes commonly used to 
manage AD in the UK; emollients and soap substitutes, oral anti-histamines, topical 
corticosteroids (TCS), topical calcineurin inhibitors (TCI), oral systemic treatments (ciclosporin, 
azathioprine, oral steroids, mycophenolate mofetil [MMF] and methotrexate), topical 
antimicrobial treatments, and phototherapy. 
 
Treatment escalation 
We will analyse three elements of treatment escalation in AD: Firstly, the proportion of people 
prescribed a potent or very potent topical steroid who have escalated from a prescription for a 
mild or moderate potency steroid in the preceding weeks. Secondly, the proportion of people 
prescribed a TCI who have escalated from potent topical steroid or less potent steroid in the 
preceding weeks. Thirdly, the proportion of people initiated on treatment with systemic 
therapies who have undergone previous treatment with phototherapy. 
 
Statistical Analyses 
Prevalence  
We will estimate time trends of the prevalence of AD by calendar year over the study period, 
overall and by age group. Prevalent individuals will be defined those fulfilling the diagnostic 
criteria for AD at the mid-point (July 1) of the calendar year in question. Prevalence will be 
calculated by dividing the number of prevalent individuals by the total number of eligible 
individuals in the study population at the same time point. In the 2017 cohort of prevalent 
individuals we will then estimate the age group stratified prevalence of AD by sociodemographic 
factors (sex, ethnicity, IMD), and geographical region. All prevalence (and incidence) estimates 
will be standardised to UK population estimates. Prevalence of moderate and severe AD within 
the AD population (denominator) will be calculated using the same approach. 
 
Incidence 
Incident cases will be defined as individuals with a first ever diagnostic Read code for AD during 
the study period. Patients with a diagnosis of AD prior to the study period will be excluded. At 

 
 
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least one year follow-up prior to the diagnosis date will be required to confirm the diagnosis was 
incident. Individuals with a diagnosis within one year of registering with a practice will be 
excluded from the incident analysis, unless under one year old. Age-standardised incidence rates 
(per 100 person-years), stratified by age, other sociodemographic factors and calendar year, will 
be calculated by dividing the number of incident patients by the sum of person-years of follow-
up for the total eligible population over the study period. Adjusted incidence rate ratios by 
sociodemographic factors will be estimated using Poisson regression.   
 
In the incident cohort with AD we will examine disease trajectories by describing the proportion 
of individuals who developed moderate and severe AD post-diagnosis. We will evaluate the 
impact of sociodemographic predictors on time to first occurrence of moderate and severe AD 
using Cox proportional hazards models. Time to return to active AD will also be evaluated in the 
subset of individuals whose disease was defined as active at diagnosis using the same approach.  
 
AD-associated conditions 
In the prevalent cohort we will describe the prevalence of AD-associated comorbidities in all 
individuals at the start of follow-up. Start of follow-up for an individual with AD will be defined 
as the latest of: 1 Jan 2008, the date of diagnosis of AD, or 365 days after practice registration. 
Prevalence estimates will be compared to those of a matched unexposed cohort without AD. The 
matched unexposed cohort will be defined by matching individuals in the exposed cohort with 
individuals without a diagnosis of AD, by age and sex at GP practice level. The start of follow-up 
for each matched individual will be the start of follow-up of their matched counterpart. 
Unexposed individuals will be required at have at least one year of follow-up in RCGP RCS when 
matched to minimise the risk they have a non-recorded existing diagnosis of AD.  
 
We will then examine the risk of new onset autoimmune conditions (RA, IBD, coeliac disease, 
type 1 diabetes, and MS) in individuals with AD without a pre-existing autoimmune condition at 
the start of follow-up compared to the matched unexposed cohort. Follow-up for all individuals 
will end at the earliest of the study end-date (January 1, 2018), the date of patient transfer from 
an included practice, date of death, or the date an individual developed an outcome of interest. 
We will include all individuals contributing at least 1 day of follow-up time in the analysis. We 

 
 
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will estimate the risk of each autoimmune condition separately using time to failure analysis. 
Initially, unadjusted Cox proportional hazards models, stratified by matched set (AD versus non-
AD), will be used to provide overall hazard ratios as summary estimates for the association of 
the presence of AD with the time to each autoimmune condition. Models were subsequently 
adjusted for duration of disease, baseline sociodemographic factors, clinical measures, and 
comorbidities in multivariable analysis. 
 
Prescribing patterns 
Within the prevalent population we will describe prescribing patterns for AD and active AD 
overall, stratified by sociodemographic factors, and as yearly time trends. Prescribing rates will 
be calculated as the number of individuals with AD receiving at least one prescription for a 
particular medication class during a year divided by the number of eligible individuals with AD 
at the mid-point of that calendar year.  
 
Treatment escalation 
For the three treatment escalation steps we will describe overall rates of stepwise escalation 
(contrasted with immediate use of more potent treatment) and rates stratified by demographic 
factors. 
 
Secondary analyses 
Secondary analyses in the form of subgroup comparisons and sensitivity analyses using 
alternative statistical approaches to evaluation will be used where appropriate to corroborate 
or further explore any unexpected findings. 
Ethical approval 
Study approval will be requested from the Research Committee of the RCGP RSC. The study does 
not meet the requirements for formal ethics board review as defined using the NHS Health 
Research Authority research decision tool (http://www.hra-decisiontools.org.uk/research/). 

 
 
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Dissemination of results 
We aim to produce high-quality publications for submission to a high impact journals. 
Contributors 
Research support for this project in several areas including data analysis, literature searching, 
and medication writing will be provided by Momentum Data. John Dennis and Andrew 
McGovern of Momentum Data have contributed to the writing of this protocol and to the study 
design. Funding for these studies has been provided by Pfizer UK. 
Scientific rigor and study registration 
The team ethos at Momentum Data is to support the highest quality research, for patient benefit, 
with rigorous scientific standards. Publication bias remains an issue in observational studies. 
Therefore, and in accordance with RCGP RSC requirements, if approval is granted the protocol 
will be registered as an observational study with ClinicalTrials.gov and made publicly available 
prior to the commencement of data analysis. Any protocol amendments will be published 
alongside this public record of the study and will be noted in any final publication with the 
rationale for the modification. Any changes will be assessed for the need for ethics approval and 
further RCGP RSC study approval; these will be sought if required. 
 
 

 
 
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