Polymyalgia rheumatica (PMR) is a common inflammatory rheumatological condition that affects people over the age of 40. PMR causes stiffness and pain in the shoulders and hips. It has been estimated that approximately 2.43% of women and 1.66% of men will develop PMR in their lifetime and that each year around 8 in every 10,000 people over 40 in the UK develop the condition. Steroid tablets are the main treatment, but some find it difficult to stop taking these medicines. Various studies have been published that suggest that people who have PMR are at an increased risk of developing heart disease, stroke and certain types of blood cancer.
The knowledge of how common PMR is, and which medical conditions may be linked with it, will lead to better diagnosis and treatment of patients with this condition. The first study will update our knowledge of the occurrence of PMR in England and Wales; this was last investigated in a study over 15 years old. Secondly, we will investigate which other medical conditions are more likely to occur in people with PMR before and after their PMR diagnosis, which will help to understand why people find it difficult to stop taking steroids.
Polymyalgia rheumatica (PMR) is a common inflammatory rheumatological condition. Treatment involves low dose glucocorticoids, and is generally effective, although some patients have problems with treatment withdrawal.
The risk of developing PMR varies depending on geographic location. The most recent data from the UK, from 1996 to 2002, showed an incidence of 8 per 10,000 per year in people aged over 40 years.
Little is known about comorbidities that may coexist with PMR. This project will 1) re-estimate the incidence and prevalence of PMR in the UK, 2) measure comorbidities before and after PMR diagnosis. For the first aim: incidence rate per 10,000 years, between 1990 and 2017; and point prevalence on 31st March 2017 will be calculated.
For the second, patients with PMR will be individually matched to four controls. Using a nested case-control study, we will calculate the prevalence of individual comorbidities for cases and controls. Odds ratios (OR) and 95% confidence intervals will be obtained using conditional logistic regression. We will then calculate the cumulative probability of each comorbidity up to 10 years after the index date using Kaplan-Meier plots for comorbidities occurring after PMR diagnosis. We will calculate hazard ratios using Cox regression model.
Alyshah Abdul Sultan - Chief Investigator - AstraZeneca Ltd - UK Headquarters
Richard Partington - Corresponding Applicant - Keele University
Christian Mallen - Collaborator - Keele University
Richard Partington - Collaborator - Keele University
Sara Muller - Collaborator - Keele University
Toby Helliwell - Collaborator - Keele University
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation