Healthcare Disparities in Alopecia Areata: UK Population-based Cohort Study
Conditions: Alopecia Areata
Sponsor: Momentum Data

 
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Study information 
Title 
Healthcare disparities in alopecia areata: UK 
population-based cohort study 
Protocol version identifier 
1.0  
Date 
02 November 2022 
NCT number 
NCT05727306 
 

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1. TABLE OF CONTENTS 
1. TABLE OF CONTENTS .......................................................................................................2 
2. LIST OF ABBREVIATIONS ................................................................................................4 
3. RESPONSIBLE PARTIES ....................................................................................................6 
4. ABSTRACT ...........................................................................................................................7 
5. AMENDMENTS AND UPDATES .......................................................................................9 
6. MILESTONES .......................................................................................................................9 
7. RATIONALE AND BACKGROUND ..................................................................................9 
8. RESEARCH QUESTION AND OBJECTIVES .................................................................10 
8.1. Study Objectives .....................................................................................................10 
8.2. Primary Objectives ..................................................................................................10 
8.2.1. Objective 1 ..................................................................................................10 
8.2.2. Objective 2 ..................................................................................................10 
8.2.3. Objective 3 ..................................................................................................10 
8.3. Secondary Objectives ..............................................................................................10 
8.3.1. Objective 4 ..................................................................................................10 
9. RESEARCH METHODS ....................................................................................................10 
9.1. Study design ............................................................................................................10 
9.1.1. Total disease burden; cumulative lifetime incidence ..................................11 
9.1.2. Disparities in the impact of AA on mental health, work impact and 
healthcare utilisation ........................................................................................11 
9.2. Setting ......................................................................................................................11 
9.2.1. AA Definition .............................................................................................11 
9.2.2. Sociodemographic subgroups .....................................................................11 
9.2.3. Inclusion criteria .........................................................................................12 
9.2.4. Exclusion criteria ........................................................................................12 
9.3. Variables ..................................................................................................................13 
9.4. Primary Endpoints ...................................................................................................14 
9.5. Secondary Endpoints ...............................................................................................15 
9.6. Data sources ............................................................................................................15 
9.7. Study size ................................................................................................................15 
9.7.1. Sample size calculations .............................................................................15 

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9.8. Data management ....................................................................................................15 
9.9. Data analysis ...........................................................................................................15 
9.10. Quality control .......................................................................................................16 
9.11. Limitations of the research methods .....................................................................16 
9.12. Other aspects .........................................................................................................17 
10. PROTECTION OF HUMAN SUBJECTS ........................................................................17 
10.1. Patient information ................................................................................................17 
10.2. Patient consent .......................................................................................................17 
10.3. Institutional review board (IRB)/Independent ethics committee (IEC) ................17 
10.4. Ethical conduct of the study ..................................................................................17 
11. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS ......................................................................................................................18 
12. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS........18 
13. REFERENCES ..................................................................................................................19 
14. LIST OF TABLES .............................................................................................................21 
15. LIST OF FIGURES ...........................................................................................................21 
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS .........................................................21 
ANNEX 3. ADDITIONAL INFORMATION .........................................................................21 
 

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2. LIST OF ABBREVIATIONS 
Abbreviation 
Definition 
AA 
Alopecia Areata 
BMI 
Body Mass Index 
CPRD 
Clinical Practice Research Datalink 
DSP 
Data Security and Protection 
EMA 
European Medicines Agency 
ENCePP 
European Network of Centres for 
Pharmacoepidemiology and Pharmacovigilance 
EQUATOR 
Enhancing the QUAlity and Transparency Of health 
Research 
ESA113 
Employment Support Allowance 
GEP 
Good Epidemiological Practice 
GP 
General Practitioner 
GPP 
Good Pharmacoepidemiology Practices 
IB113 
Incapacity benefit 
ICD10 
International Statistical Classification of Diseases and 
Related Health Problems 10th Revision 
IEA 
International Epidemiological Association 
IMD 
Index of Multiple Deprivation 
ISPE 
International Society for Pharmacoepidemiology 
ISPOR 
Pharmacoeconomics and Outcomes Research 
NHS 
National Health Service 
OPCRD 
Optimum Patient Care Research Database 
RCGP RSC 
Royal College of General Practitioners Research and 
Surveillance Centre 

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SAP 
Statistical Analysis Plan 
SD 
Standard Deviation 
SES 
Socioeconomic Status 
THIN 
The Health Improvement Network 
UK 
United Kingdom 
US 
United States 
 
 
 

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3. RESPONSIBLE PARTIES 
Principal Investigator(s) of the Protocol 
Name, degree(s) 
Job Title 
Affiliation 
Address 
Mr. John Nesnas, MPharm 
Medical Team Leader at 
Pfizer 
Pfizer Ltd 
Walton Oaks, Walton on the Hill, 
Tadworth, Surrey, KT20 7NS, 
UK 
Dr John Dennis, PhD 
Head of Research at 
Momentum Data 
Momentum Data 
Ltd 
Pendragon House, 
65 London Road,  
St. Albans,  
Hertfordshire,  
AL1 1LJ, UK 
Dr Andrew McGovern, 
MD(Res) 
Scientific Director at 
Momentum Data 
Momentum Data 
Ltd 
Pendragon House, 
65 London Road,  
St. Albans,  
Hertfordshire,  
AL1 1LJ, UK 
 
 

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4. ABSTRACT 
Report title: 
Healthcare disparities in alopecia areata: UK population-based cohort study 
 
Version: 
1.0 
 
Protocol date: 02 November 2022 
 
Main author: Mr. John Nesnas, Pfizer Ltd. 
 
Rationale and background: 
 
Alopecia areata (AA) is a common, immune-mediated non-scarring form of alopecia. Our previous 
work has provided the most comprehensive analysis of the epidemiology of AA to date. We found 
that AA is more common in people of lower socioeconomic status and in people from Black, Asian, 
and mixed ethnic groups compared to those of White ethnicity. However, these data formed a small 
component of the initial study and there is substantial scope to expand on these initial data to provide 
a greater understanding of the total disease burden across these groups including reporting lifetime 
risk estimates. 
 
Research question and objectives: 
 
The overall purpose of the study is to provide an estimate of the cumulative lifetime incidence of AA 
in the population overall and by (important) sociodemographic groups. Moreover, to do a subgroup 
analysis in the AA population to identify health-related disparities across people in different 
socioeconomic strata, geographical distribution, sex and ethnic groups. 
 
Study Design: 
 
The study will use retrospectively collected anonymised data from all eligible patients in the Oxford-
Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) dataset at 
the date of data extraction. A cross-sectional design (incidence) will be used to assess the total 
disease burden of AA, stratified by sociodemographic groups. A matched-cohort design will be used 
for incidence of AA related: Mental health conditions; work impact; healthcare utilisation. 
 
Population: 
 
The cohort for this study will consist of all adults and children (aged 12+) contributing to RCGP 
RCS database during the study period (between January 1, 2009 and December 31, 2018 inclusive). 
People diagnosed with AA will be identified using diagnosis codes specific to the condition. 
 
Variables: 
 
Exposure: People diagnosed with AA as defined by clinical diagnosis codes. 

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Outcomes: For the impacts of AA on different sociodemographic groups assessment outcomes will 
comprise: incidence of AA, depressive episodes, recurrent major depression, anxiety disorders, 
dermatology referrals, primary care visits, referrals for psychological therapy, psychiatric reviews, 
time off work for illness and unemployment. 
 
Covariates: Three different adjustment sets will be used for each endpoint analysis. These include: 
an unadjusted model, a sex and age adjusted model, and a multivariable model with an adjustment 
set of: body mass index (BMI), smoking status, alcohol use, and common comorbidities: type 2 
diabetes, hypertension, atrial fibrillation, angina, acute myocardial infarction, stroke, heart failure, 
chronic liver disease, dementia, rheumatoid arthritis, asthma, chronic obstructive pulmonary disease, 
chronic kidney disease, malignancy and inflammatory bowel disease. 
 
Data sources: 
 
The RCGP RSC is the longest running primary care network in the UK, collecting weekly data since 
1964. The RCGP RSC database contains complete data on all events and clinical entities coded in 
UK primary care. 
 
Study size: 
 
The RCGP RSC cohort is drawn from a large GP practices network across England, currently 
covering a registered population of 2.6 million people, representing a broadly representative sample 
of the UK. 
 
Data Analysis: 
 
Cumulative lifetime incidence of AA will be estimated using cases of incident AA occurring during 
the observational study period (January 1, 2009 and December 31, 2018). For all analyses, the 
overall results including both adults (aged 18+) and children (aged 12-17) will be published, with 
stratification by sex, ethnicity, deprivation quintile, geographic region and urban/rural classification. 
The assessment of any associations with baseline characteristics and the outcomes of interest will be 
assessed using Cox proportional hazards models (time to event outcomes) and Poisson regression 
(repeated event outcomes) models. Three different adjustment sets will be used for each endpoint 
analysis. 
 

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5. AMENDMENTS AND UPDATES 
None 
 
6. MILESTONES 
Milestone 
Planned date 
Start of data collection  
25-October-2022 
End of data collection  
24-January-2023 
Study progress report 
29-November-2022 
Final study report 
21-February-2023 
 
7. RATIONALE AND BACKGROUND 
Alopecia areata (AA) is a common, immune-mediated non-scarring form of alopecia. Our previous 
work has provided the most comprehensive analysis of the epidemiology of AA to date1. This study 
demonstrated that the incidence of AA is 0.26 per 1,000 person-years in the UK (United Kingdom), 
with a peak incidence at age 25-29; however incident AA occurs across the lifespan. We found that 
AA is more common in people of lower socioeconomic status and in people from Black, Asian, and 
mixed ethnic groups compared to those of White ethnicity2. However, these data formed a small 
component of the initial study and there is substantial scope to expand on these initial data to provide 
a greater understanding of the total disease burden across these groups including reporting lifetime 
risk estimates. Current lifetime risk estimates are taken from a single population-based study with 
just 530 AA cases in a single region of the United States (US)3 and most reported age, sex and 
ethnicity prevalence estimates that have been produced from studies performed in secondary care4-8. 
These studies are likely to be missing a large proportion of cases and therefore substantially 
underestimate the total disease burden in these groups. 
 
Our previous work strongly suggested there are significant socioeconomic and ethnic disparities in 
healthcare and outcomes in people with AA. A comprehensive assessment of these potential 
disparities in AA is needed, this would strongly complement the existing work and support the use 
of newer therapies in AA. 
 
Our previous work has also demonstrated that AA is associated with significant psychological 
consequences including an increased incidence of depression and anxiety9. These data suggest a 
socioeconomic gradient in the mental health impacts of AA (with AA associated with a greater 
mental health burden in those with lower socioeconomic status). However, the study was not 
designed to assess this as a primary outcome, and further analysis is required to fully understand 
these potential relationships. 

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8. RESEARCH QUESTION AND OBJECTIVES 
8.1. Study Objectives 
The overall purpose of the study is to provide an estimate of the cumulative lifetime incidence of AA 
in the population overall and by sociodemographic groups (sex, ethnicity, deprivation, geographic 
location and urban-rural status). Moreover, to perform a subgroup analysis in the AA population to 
identify health-related disparities across people in different socioeconomic strata, geographical 
distribution, sex and ethnic groups. The disparities that will be considered are AA associated: Mental 
health conditions; healthcare utilisation; and work impact (time off work and unemployment). 
 
8.2. Primary Objectives 
8.2.1. Objective 1 
Describe the total burden of AA (cumulative lifetime incidence) across sociodemographic groups 
(including geographical distribution). 
 
8.2.2. Objective 2 
Describe any disparities in AA related mental health conditions across sociodemographic groups. 
 
8.2.3. Objective 3 
Describe any disparities in AA healthcare utilisation across sociodemographic groups. 
 
8.3. Secondary Objectives 
8.3.1. Objective 4 
Describe any disparities in AA related work impact (time off work and unemployment) across 
sociodemographic groups. 
 
9. RESEARCH METHODS  
9.1. Study design  
The study will use retrospectively collected anonymised data from all eligible patients in the Oxford-
Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) dataset at 
the date of data extraction. The cohort to be used for this study has already been specified for 
previous work as follows: 
All adults and adolescents (aged 12+) registered with practices contributing data to RCGP RCS 
between January 1, 2009 and December 31, 2018, will be eligible for inclusion in the study. People 
who have opted out of record sharing will not be included (approximately 1.8% of the adult 
population) and have not been uploaded to the RCGP RCS database. Cumulative lifetime incidence 
of AA will be estimated using cases of incident AA occurring during the observational study period 
(January 1, 2009 and December 31, 2018). For all analyses, the overall results including both adults 

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(aged 18+) and children (aged 12-17) will be published, with stratification by sex, ethnicity, 
deprivation quintile, geographic region and urban/rural classification. 
 
The assessment of any associations with baseline characteristics and the outcomes of interest 
(objectives 2-4) will be assessed using Cox proportional hazards models (time to event outcomes) 
and Poisson regression (repeated event outcomes) models. Three different adjustment sets will be 
used for each endpoint analysis. These include: an unadjusted model, a sex and age adjusted model, 
and a multivariable model with an adjustment set of: body mass index (BMI), smoking status, 
alcohol use, and common comorbidities: type 2 diabetes, hypertension, atrial fibrillation, angina, 
acute myocardial infarction, stroke, heart failure, chronic liver disease, dementia, rheumatoid 
arthritis, asthma, chronic obstructive pulmonary disease, chronic kidney disease, malignancy and 
inflammatory bowel disease. 
 
9.1.1. Total disease burden; cumulative lifetime incidence 
A cross-sectional design (incidence) will be used to assess the total disease burden of AA, stratified 
by sociodemographic groups. 
 
9.1.2. Disparities in the impact of AA on mental health, work impact and healthcare utilisation 
A matched-cohort design will be used for incidence of AA related: Mental health conditions; work 
impact; healthcare utilisation. 
 
9.2. Setting 
The RCGP RSC cohort is drawn from a large GP practices network across England, currently 
covering a registered population of 2.6 million people, representing a broadly representative sample 
of the UK.10  
 
9.2.1. AA Definition 
People diagnosed with AA will be identified using diagnosis codes specific to the condition.11 
People will be considered to have an AA diagnosis if they had an AA specific diagnosis code and, in 
the subsequent 365 days, no code for an alternative diagnosis (scarring alopecia12, traction alopecia, 
congenital alopecia, androgenetic alopecia, telogen effluvium, tinea capitis, trichotillomania, or 
secondary syphilis of the scalp).  
 
Incident cases will be defined as people with a first ever diagnosis code of AA during the study 
period. People with a diagnosis of AA prior to the study period will be excluded. To increase 
certainty that an AA diagnosis was incident, those diagnosed within six months of registering with a 
practice will be excluded. 
 
9.2.2. Sociodemographic subgroups 
Age, sex, socioeconomic status, ethnicity, major regions of England and urban/rural classification 
will comprise the sociodemographic factors used for stratification of the outcome measures.  

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Ethnicity will be grouped using the standardised definitions of major UK ethnic groups: Black, 
Asian, White mixed, and others.13 
 
Socioeconomic status (SES) will be defined using the national deprivation measure; index of 
multiple deprivation (IMD) and stratified into quintiles of deprivation according to the national 
distribution.14 IMD is calculated at the point of data extraction, using patient postcode. 
 
Age will be stratified into four age categories: children aged 12-17, 18-29, 30-49 and 50+ based on 
our previous research into incidence of AA.2 
 
Geographical distribution will consist of two subgroups including; geographic region and urban/rural 
classification. Geographic region within England comprises; Greater London, South East, South 
West, West Midlands, North West, North East, Yorkshire and the Humber, East Midlands, and East 
of England.  
 
9.2.3. Inclusion criteria 
Patients must meet all of the following inclusion criteria to be eligible for inclusion in the study: 
1. The cohort for this study will consist of all adults and children (aged 12+) contributing to RCGP 
RCS database during the study period (between January 1, 2009 and December 31, 2018 
inclusive).  
2. The AA population consists of patients newly diagnosed with AA at any point during the study 
period. 
 
9.2.4. Exclusion criteria 
Patients meeting any of the following criteria will not be included in the study: 
1. People with the alternative non-AA diagnoses (section 9.2.1). 
2. People with AA diagnosis within 6 months of registration. 
3. People with less than 1 year of follow up within the dataset. 
4. People over the age of 95. 
 
 

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9.3. Variables 
The variables to be utilised are listed below: 
Variable 
Role 
Operational definition 
Age 
Baseline characteristic, subgroup variable, and 
potential confounder  
Age will be defined as of the index date.  
Sex 
Baseline characteristic, subgroup variable, and 
potential confounder 
Identified from primary care records using 
clinical codes. 
Socioeconomic deprivation 
Baseline characteristic, subgroup variable and 
potential confounder 
Defined using the Index of Multiple 
Deprivation which is divided into national 
quintiles. 
Ethnicity 
Baseline characteristic, subgroup variable, and 
potential confounder 
Identified from primary care records using 
clinical codes. 
UK geographic region  
Baseline characteristic, subgroup variable, and 
potential confounder 
The United Kingdom will be divided into nine 
regions: Greater London, South East, South 
West, West Midlands, North West, North East, 
Yorkshire and the Humber, East Midlands, and 
East of England. Geographic region will be 
captured from enrollment data. 
Urban/Rural classification 
Baseline characteristic, subgroup variable, and 
potential confounder 
Defined as urban or rural area which will be 
captured from enrollment data. 
Alopecia Areata 
Case definition 
Identified from primary care records using 
clinical codes. 
Depressive episodes 
Outcome 
Defined by the International Statistical 
Classification of Diseases and Related Health 
Problems 10th Revision (ICD10) classification, 
and identified using algorithms validated or use 
in UK primary care data. 
Recurrent major depression 
Outcome 
Defined by the International Statistical 
Classification of Diseases and Related Health 
Problems 10th Revision (ICD10) classification, 
and identified using algorithms validated or use 
in UK primary care data. 
Anxiety disorders 
Outcome 
Defined by the International Statistical 
Classification of Diseases and Related Health 
Problems 10th Revision (ICD10) classification, 
and identified using algorithms validated or use 
in UK primary care data. 
Dermatology referrals 
Outcome 
Identified from primary care records using 
clinical codes. 
Primary care visits 
Outcome 
Identified from primary care records using 
clinical codes. 
Referrals for psychological 
therapy 
Outcome 
Identified from primary care records using 
clinical codes. 
Psychiatric reviews 
Outcome 
Identified from primary care records using 
clinical codes. 
Time off work for illness 
Outcome 
Defined using primary care codes for ‘sick 
leave’ or the issuing of a Med 3 certificate 
indicating time off work for illness 
Unemployment 
Outcome 
Defined using primary care codes indicating 
unemployment or incapacity from work (IB113 
[incapacity benefit] form or ESA113 form 
[Employment Support Allowance, which 
replaced IB113 from January 2011]) 
Body mass index 
Potential confounder 
Identified from primary care records using 
clinical codes. 

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Smoking status 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Alcohol use 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Type 2 diabetes 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Hypertension 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Atrial fibrillation 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Angina 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Acute myocardial infarction 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Stroke 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Heart failure 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Chronic liver disease 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Dementia 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Rheumatoid arthritis 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Asthma 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Chronic obstructive 
pulmonary disease 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Chronic kidney disease 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Malignancy 
Potential confounder 
Identified from primary care records using 
clinical codes. 
Inflammatory bowel disease 
Potential confounder 
Identified from primary care records using 
clinical codes. 
 
9.4. Primary Endpoints 
Objective 1: An incident diagnosis of AA is the date of the first diagnosis code in the record and no 
alternative diagnosis that merits exclusion (any form of scarring alopecia12, traction alopecia, 
congenital alopecia, androgenetic alopecia, telogen effluvium, tinea capitis, trichotillomania, or 
secondary syphilis of the scalp) diagnosed in the subsequent 365 days from date of AA diagnosis. 
Objective 2: Mental health condition outcomes will be assessed up to two years post-AA diagnosis 
and will comprise new onset depressive episodes, recurrent major depression, and anxiety disorders, 
defined by the International Statistical Classification of Diseases and Related Health Problems 10th 
Revision (ICD10) classification, and identified using algorithms validated for use in UK primary 
care data. 
 
Objective 3: Healthcare utilisation outcomes will comprise primary care visits, dermatology 
referrals, referrals for psychological therapy (including those via IAPT; Improving Access to 
Psychological Therapies) and psychiatric reviews in the two years post AA diagnosis. 
 

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9.5. Secondary Endpoints 
Unemployment in the two years post-AA diagnosis will be identified using Read codes relating to 
unemployment recorded in the primary care record or the issuing of IB113 or ESA113 forms. 
 
Time off work in the two years post-AA diagnosis will be indicated by the issuing of Med 3 
certification from primary care (Statement of Fitness for Work certification). 
  
9.6. Data sources  
The RCGP RSC is the longest running primary care network in the UK, collecting weekly data since 
1964. The RCGP RSC database contains complete data on all events and clinical entities coded in 
UK primary care. These include demographic information, clinical diagnoses, laboratory test results, 
primary care issued prescriptions, process of care codes (e.g. specialist dermatology reviews), and 
anthropometric measurements (e.g. BMI), and are coded using the Read Coding system.15  
 
9.7. Study size 
9.7.1. Sample size calculations 
A sample size calculation is only applicable to the incidence of mental health conditions of anxiety 
and depression in people diagnosed with AA.  
 
Assuming 80% power, a 5% level of statistical significance and a background population prevalence 
of 15% for anxiety and 10% for depression,16 our anticipated sample size for AA (n = 6007) would 
be sufficient to detect a risk difference of 1.2% in depression between those with and without AA, 
and 1.5% difference in anxiety between those with and without AA. Sample size calculations were 
performed in OpenEpi,17 results are presented using methods of Kelsey.18 
 
9.8. Data management  
This study will utilise the previously extracted data from our previously published study.9 Individual 
patient data was anonymized at the point of data extraction. All data will remain in anonymized form 
and will be held on a secure server at the University of Oxford. The data will not be used for any 
purposes other than for the research which is described in the respective protocols and which has 
been approved by the RCGP RSC Research Committee. The sponsor, Pfizer Ltd, will not have 
access to the individual anonymised patient data.  
 
All statistical analyses will be performed using R version 4.2.1. 
 
9.9. Data analysis  
Detailed methodology for summary and statistical analyses of data collected in this study will be 
documented in a statistical analysis plan (SAP), which will be dated, filed and maintained by the 
sponsor.  The SAP may modify the plans outlined in the protocol; any major modifications of 
primary endpoint definitions or their analyses would be reflected in a protocol amendment. 

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9.10. Quality control 
The sponsor delegates the conduct of this study to Momentum Data. The Momentum Data team will 
have full access to all the anonymized data in the study and all employees have completed 
information governance, information security, and data protection training provided by the 
University of Oxford and NHS (National Health Service) Digital. Data will be controlled in 
accordance with data protection legislation, protocols and policies of Momentum Data and NHS 
policies and processes, as defined in the NHS Data Security and Protection [DSP] toolkit for 
research and information governance. The research team at Momentum Data have extensive 
experience in working with routine healthcare data and have all completed relevant advanced 
degrees and have extensive experience using various large healthcare data sources from the UK 
including CPRD (Clinical Practice Research Datalink), The Health Improvement Network (THIN), 
RCGP RSC database, Optimum Patient Care Research Database (OPCRD), and others. 
All codes lists utilised for data extraction will undergo the rigorous quality control process utilised 
by Momentum Data for multiple real world evidence studies. This process consists of manual code 
list generation by a coding expert with a clinical background. The list is then independently reviewed 
by a second coding expert. The lists then go through an automated quality control process to identify 
any potential formatting errors or coding inconsistencies. During the data extraction process, high 
frequency codes are independently reviewed by a third reviewer to ensure that the most commonly 
used codes correctly match the clinical entity they are being used to identify. A fourth quality control 
step may also be used to look for overlap between code or case definitions where multiple 
definitions are possible e.g., biochemical disease markers and clinical diagnosis codes for a 
condition. Finally once variables have been generated, the frequency and pattern of variable 
prevalence is compared with known data from previous analysis in other independent datasets and 
published literature. Any inconsistencies are reviewed and investigated as appropriate. 
Statistical programming output is quality controlled by an independent statistical programmer. All 
final study outputs including tables and figures are subject to quality control review by two 
independent reviewers. 
 
9.11. Limitations of the research methods 
Disparities between sociodemographic subgroups will be interpreted based on the assumption of the 
primary/secondary outcomes being related to the AA. We have no definite way to identify that every 
occurrence of an outcome is related to AA in the context of healthcare utilisation and work impact 
outcomes. 
 
This is an ecological study limited to the UK population and may not be generalisable to other 
populations. 
 
We expect a substantial amount of missing data for the ethnicity variable which is a limitation of the 
dataset itself and could result in bias. Necessary sensitivity analyses will be undertaken to 
circumvent this and limit any impact this could have in our analysis.  

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We will perform additional exploratory analysis into the time between dermatology referral and 
dermatology review with the goal of potentially identifying NHS and private referrals and exploring 
regional differences. If this data is sufficient, based on provisional analysis, we will include 
additional study endpoints using this lag time between referral and dermatology review. 
 
9.12. Other aspects 
Not applicable 
 
10. PROTECTION OF HUMAN SUBJECTS 
10.1. Patient information  
This study involves data that exist in anonymised structured format and contain no patient personal 
information.  
 
10.2. Patient consent 
As this study involves anonymised structured data, which according to applicable legal requirements 
do not contain data subject to privacy laws, obtaining informed consent from patients by Pfizer is not 
required. 
 
10.3. Institutional review board (IRB)/Independent ethics committee (IEC) 
There must be prospective approval of the study protocol, protocol amendments, and other relevant 
documents (e.g., informed consent forms if applicable) from the relevant IRBs/IECs.  All 
correspondence with the IRB/IEC must be retained.  Copies of IRB/IEC approvals must be 
forwarded to Pfizer.  
 
10.4. Ethical conduct of the study 
The study will be conducted in accordance with legal and regulatory requirements, as well as with 
scientific purpose, value and rigor and follow generally accepted research practices described in: 
• Guidelines for Good Pharmacoepidemiology Practices (GPP). Public Policy Committee, 
International Society of Pharmacoepidemiology. Pharmacoepidemiology and Drug Safety 
2015; 25:2-10. 
• Good Practices for Outcomes Research issued by the International Society for 
Pharmacoeconomics and Outcomes Research (ISPOR) 

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• Good practices for real-world data studies of treatment and/or comparative effectiveness: 
Recommendations from the joint ISPOR-ISPE Special Task Force on real-world evidence in 
healthcare decision making 
• International Ethical Guidelines for Epidemiological Studies issued by the Council for 
International Organizations of Medical Sciences (CIOMS) 
• European Medicines Agency (EMA) European Network of Centres for 
Pharmacoepidemiology and Pharmacovigilance (ENCePP) Guide on Methodological 
Standards in Pharmacoepidemiology 
• Good Epidemiological Practice (GEP) guidelines issued by the International Epidemiological 
Association (IEA).  
• Study reporting will be conducted in accordance with the relevant EQUATOR (Enhancing 
the QUAlity and Transparency Of health Research) guidelines. 
 
11. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE REACTIONS  
Adverse event (AE) /adverse reaction reporting is not required for this study design. It will not be 
possible to identify AEs from the data captured for this study.  
This study involves data that exist as structured data by the time of study start. It is not possible to 
link (i.e., identify a potential association between) a particular product and medical event for any 
individual. Thus, the minimum criteria for reporting an AE (i.e., identifiable patient, identifiable 
reporter, a suspect product, and event) cannot be met. 
 
12. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS 
A final study manuscript will be developed for submission to a scientific peer reviewed journal. 
Additional study outputs may be presented at conferences and/or scientific symposia. 
In the event of any prohibition or restriction imposed (e.g., clinical hold) by an applicable competent 
authority in any area of the world, or if the investigator is aware of any new information which 
might influence the evaluation of the benefits and risks of a Pfizer product, Pfizer should be 
informed immediately.  
 
 

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14. LIST OF TABLES  
No study tables are included 
 
15. LIST OF FIGURES 
No figures are included 
 
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS 
None 
 
ANNEX 3. ADDITIONAL INFORMATION 
Not applicable.