Myasthenia gravis (MG) is a long-term neuromuscular autoimmune disease characterised by varying degrees of muscle weakness. Symptoms can range from double vision and drooping eyelids to difficulty swallowing and complete paralysis of the breathing muscles - known as a myasthenic crisis, which requires intensive care and machines to help patients breathe. There are a number of existing treatments for MG, but many patients continue to experience symptoms, and many immunosuppressant medications are associated with increased risks of serious infections.
Whilst MG patients with crisis are known to have a high burden of healthcare, it isn’t well known what the other drivers of healthcare usage and costs are outside of a crisis are, including how that compares to patients without MG.
This study will describe the current treatment pathway for MG patients in England, looking at how and when patients are treated with different therapies, and compare the healthcare burden of these patients to a group of similar patients without MG. Understanding this will allow for healthcare resources to be prioritised to and improve the clinical outcomes of MG patients.
Current clinical standards of care for MG include acetylcholinesterase inhibitors, steroids, immunosuppressants and, in the case of hospitalisation for myasthenic crisis, intravenous immunoglobulin (IVIG) and plasmapheresis [1–4]. Many patients treated with these continue to experience symptoms and these medications can increase susceptibility to serious infections. There is a significant unmet need for therapies with sustained clinical benefit and a need for understanding how MG-related healthcare resource usage (HCRU) compares to patients without MG throughout the full clinical pathway, outside of crisis.
Whilst MG patients with myasthenic crisis are known to have high HCRU, it is currently unknown what the drivers of HCRU are along the MG treatment pathway or how that HCRU compares to matched controls. In order to inform healthcare policy where efficiencies can be made in treating and managing MG, there is a need to describe the current treatment pathway for patients diagnosed with MG, and to quantify their HCRU and associated costs.
This study aims to form a cohort of MG patients, included using diagnosis codes from primary and secondary care, stratified into sub-cohorts according to their peak non-crisis annualised HCRU. We shall describe demographic and clinical characteristics of MG patients, describe their HCRU, and sequence lines of therapy. Outcomes will be described as total, means, medians, percentage or rates as appropriate. HCRU and associated costs for MG patients across primary and secondary care will be compared to a matched control cohort of patients without MG using generalised linear models and estimated marginal means, where appropriate. Cohort formation will use both the CPRD-Aurum dataset linked to HES, with death data linked via the ONS Death Registry. CPRD-HES-ONS linkage allows for a description of clinical outcomes, and HCRU and associated costs across both primary and secondary care, ensuring the full clinical pathway of patients is accurately described.
Total number of MG patients; Demographics (Mean and median age on inclusion, age distribution by decade, sex distribution, deprivation, Charlson co-morbidity score distribution, mean and median follow-up, total and mean admitted time, smoking status, index of multiple deprivation quintile distribution); presence of co-morbidities prior to inclusion (diabetes, coronary artery disease, ischaemic heart disease, hypertension, stroke, hypoparathyroidism, asthma, COPD, rheumatoid arthritis, systemic lupus erythematosus, osteoporosis); admissions to critical care unit per patient per year of follow-up; treatments and therapies per patient, and line of therapy recorded at (steroids, immunotherapy , intravenous immunoglobulin, rituximab, plasmapheresis or plasma exchange, thymectomy); time on treatment in days (where applicable); number of patients and number of prescriptions recorded in primary care for immunotherapy products; healthcare resource outcomes (prescriptions issued in primary care, GP appointments in primary care, number of inpatient admissions, inpatient length of stay, inpatient HRG tariffs, number of outpatient appointments, outpatient HRG tariffs, number of A&E attendance, A&E HRG tariffs );
Jennifer Davidson - Chief Investigator - Health iQ Ltd ( UK ) t/a CorEvitas
Jennifer Davidson - Corresponding Applicant - Health iQ Ltd ( UK ) t/a CorEvitas
Archie Farrer - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Boglarka Kovacs - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Gulsah Akin Unal - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Judith Ruzangi - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Mico Hamlyn - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Seth Jarvis - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Gulsah Akin Unal - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation