Rheumatic and musculoskeletal diseases (RMDs) are a group of more than 200 disorders which are associated with increased disability and death. Most people with RMDs also have other diseases or are even at increased risk to develop these diseases. These conditions are believed to be common, but existing figures are inaccurate and the data used to produce them is often of low quality.
This study will calculate the number of adults (aged 18 or over) who are currently living with two RMD conditions, Psoriatic Arthritis and Fibromyalgia/Chronic Widespread Pain and the impact they have on the individual. We will use the information available in CPRD to identify people who have our conditions of interest and calculate how common they are in the UK population. We will also investigate whether the conditions are more or less common among certain groups, based on age, sex, socioeconomic status and what area of the UK they live in.
We will then use data from pre-existing cohort studies to determine the proportions and characteristics of people currently living with the most severe and impactful disease (e.g. high pain, high fatigue and greatest impact on activities of daily living). From here, we will calculate the number of people who are not receiving adequate support for, and relief from, their condition. The results can then be used by local councils, governments, patient groups and charities to help improve quality of life and patient outcomes for those living with RMDs conditions across the UK, by providing better support.
Rheumatic and musculoskeletal diseases (RMDs) affect ~18.8 million people in the UK. Data about the incidence, prevalence and impact of RMDs is important for workforce/service planning, healthcare budgeting and provision of support. However, the data quality and accuracy behind existing figures is unknown. Further, limited data are available at a population level to understand the impact of RMDs on daily life.
This project will develop an analysis package/framework for estimating the prevalence, incidence and impact of RMDs condition and demonstrate its performance in two exemplar conditions: Psoriatic Arthritis (PsA) and Fibromyalgia/Chronic Widespread Pain (FM/CWP).
Case identification
Cases of adults (aged 18 years and older) with PsA and FM/CWP will be identified in CPRD. Read codes will identify 1) cases with a formal diagnosis (e.g. PsA Read codes present) and 2) cases identified with a bespoke algorithm based diagnoses (e.g. codes for psoriasis + arthritis + treatment used in PsA present).
Incidence and prevalence estimation
We will use a two-step Bayesian approach using data from CPRD and prior distributions.
1. The prior distribution of the true prevalence, sensitivity, and specificity of the case identification algorithm will be estimated based on a systematic review and analysis of Manchester Integrated Healthcare Record (MIHR)
2. Prevalence and incidence rates will be calculated, stratified by age, sex, socioeconomic status, and region.
Supplementary analysis of MIHR will identify further model refinements needed to improve the precision of estimates.
Impact estimation
We will use a two-step out-of-sample prediction approach:
1. Pre-existing (unlinked) cohort data will be used to estimate and characterise the proportion of people living with the most severe and impactful disease (e.g. high pain, high fatigue and greatest impact on activities of daily living).
2. Multilevel modelling will predict impact in the general population based on these figures and the prevalence estimates identified above.
- Occurrence and impact of Psoriatic Arthritis
- Occurrence and impact of Fibromyalgia/Chronic Widespread Pain
John McBeth - Chief Investigator - University of Manchester
Yuanyuan Zhang - Corresponding Applicant - University of Manchester
Belay Yimer - Collaborator - University of Manchester
Jenny Humphreys - Collaborator - University of Manchester
Katie Druce - Collaborator - University of Manchester
Kimme Hyrich - Collaborator - University of Manchester
Ramiro Bravo - Collaborator - University of Manchester
Suzanne Verstappen - Collaborator - University of Manchester
William Dixon - Collaborator - University of Manchester
Practice Level Index of Multiple Deprivation