Epidemiology and healthcare resource utilisation associated with Duchenne muscular dystrophy

Study type
Protocol
Date of Approval
Study reference ID
21_000470
Lay Summary

Duchenne muscular dystrophy (DMD) is a rare disease that predominantly affects males and becomes evident in early childhood at around 2 to 4 years of age. DMD is caused by a mutation in a person’s genes which means they do not produce a chemical called dystrophin. Dystrophin helps protects muscle tissue and as a result patients with DMD have weaker muscles which can be easily damaged. Initially, patients may have impaired mobility and by the time of their teenage years, most will require a wheelchair. Ultimately all muscles will be affected including those that are part of the respiratory and cardiac system. In this study we wish to use the Clinical Practice Research Datalink Aurum dataset to select patients with DMD and then to describe how many patients have the condition (the prevalence) and how many new cases occur every year (the incidence). We then wish to describe how often these patients are in contact with general practice and hospital services and how much these services cost and how these costs compare to people of the same age without DMD. Furthermore, based on the available data we wish to estimate how these contacts and costs change when patients become non-ambulatory, that is dependent on a wheelchair. As a further objective, we would like to also select female carriers of the dystrophin mutation to see how this impacts upon their long term health outcomes compared with age-matched controls.

Technical Summary

NB MBL no longer required.
This study aims to describe the prevalence and incidence of Duchenne muscular dystrophy (DMD) and to estimate resource utilisation and associated costs associated with the condition compared to controls and also by severity of DMD proxied by ambulatory status. In addition, we wish to the understand long term health outcomes (cardiomyopathy and mortality) in female carriers of the dystrophin gene mutation. Patients with DMD and female carriers of the dystrophin mutation that are eligible for HES linkage, will be selected by medcode in the CPRD AURUM (Observation and Referral tables) For the DMD patient analysis, point prevalence will be calculated for 2020 for all patients registered at an Aurum practice on 30th June 2020. Incidence of DMD will be described from 2010-20 based on patients registered at a contributory practice on their birth year. Non-DMD exposed controls will be matched by primary care practice, age, gender and current practice registration. Inpatient, outpatient and accident and emergency contacts will be extracted from the relevant linked Hospital Episode Statistics (HES) datasets and costed using standard NHS tariffs. Rates will be compared with non-exposed controls using Poisson distribution and associated costs will be compared using the Gamma distribution. Patients will be classified by ambulatory status based on relevant medcodes in the Aurum dataset and/or ICD-10 codes in the HES inpatient dataset and, in a sensitivity analysis, by age, and changes in primary and secondary care resource use and associated costs compared. For females carriers of the dystrophin gene mutation, non-exposed controls will be matched by age, primary care practice and current registration and crude rates of cardiomyopathy (attributed from either the Aurum Observation table or HES admitted patient care dataset) and mortality presented and time to event using a Cox Proportional Hazards Model.

Health Outcomes to be Measured

Prevalence; incidence; health resource utilisation; costs; cardiomyopathy; survival

Collaborators

Christopher Morgan - Chief Investigator - Pharmatelligence Limited t/a Human Data Sciences
Christopher Morgan - Corresponding Applicant - Pharmatelligence Limited t/a Human Data Sciences
Emily Crossley - Collaborator - Duchenne UK
Melissa Perry - Collaborator - Pharmatelligence Limited t/a Human Data Sciences

Former Collaborators

Melissa Perry - Collaborator - Pharmatelligence Limited t/a Human Data Sciences

Linkages

HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation