Asthma is a common condition in the UK, around one-third of adults with asthma carry excess weight, of whom nearly half have diabetes. Unfortunately, treating their asthma with asthma medication is often unsuccessful, so they suffer from frequent symptoms and asthma attacks. Recently, some studies found that some diabetes medications reduce the risk of asthma attacks. But these studies alone do not provide enough evidence for doctors to advise adding these medications to treat asthma. To obtain more rigorous evidence, we will undertake a study that will examine much larger numbers of patients’ medical records than previous studies and will consider more factors that might cause asthma attacks. The most commonly used diabetic drug, metformin, is cheap and so safe that it can be used in pregnancy. Metformin is also used to treat a condition called polycystic ovary syndrome which affects fertility and puts women at greater risk of developing asthma. We will therefore additionally examine their medical records to investigate if metformin reduces the risk of asthma attacks in polycystic ovary syndrome. If the data analysis provides findings that we can be confident in, the information could be used in national asthma treatment guidelines.
The aim of this study is to determine the effectiveness of diabetes medications to reduce asthma attacks. To do this, we will draw a cohort of adult asthma patients between 2004 and 2021. The exposure will be diabetes medication use, either metformin, GLP1-RA and/or SGLT2 inhibitors. The outcome will be asthma attacks. These will be defined as either managed using oral corticosteroids from their GP, an A&E or hospital admission (HES), or death (ONS). We will assess the real-world effectiveness of each of the diabetes medications to reduce asthma attacks in patients with asthma and diabetes. We will also assess the effectiveness of metformin in reducing asthma attacks in patients with asthma and polycystic ovary syndrome. To do this we will use two methods (a) self-controlled case series design and conditional Possion regression, this methodology implicitly removes time-invariant confounding, e.g. socioeconomic status, genetics, metabolic dysfunction and is well suited for pharmacoepidemiology studies, (b) propensity score matched cohort where exposed patients will be those with incident use of the diabetes drug. We will also determine if associations between diabetes medication and asthma attacks are modified by gender, body mass index, weight loss, or type-2 inflammation. The public health benefit is to provide additional and robust evidence regarding the use of these therapeutics in asthma management.
Asthma attacks
Chloe Bloom - Chief Investigator - Imperial College London
Chloe Bloom - Corresponding Applicant - Imperial College London
Bohee Lee - Collaborator - Imperial College London
Ernie Wong - Collaborator - Imperial College Healthcare NHS Trust
Mark Cunningham - Collaborator - Imperial College London
Tricia Tan - Collaborator - Imperial College London
Bohee Lee - Collaborator - Imperial College London
Pak Lim Tse - Collaborator - Imperial College London
HES Accident and Emergency;HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation