It is well accepted that having chronic diseases like diabetes can increase the chance of developing some infectious diseases like tuberculosis. However, very few studies have evaluated whether having a serious infectious disease such as tuberculosis might increase the likelihood of subsequently developing some other chronic diseases (like diabetes, heart attacks and strokes, and other respiratory problems) even after a patient with tuberculosis has been successfully treated and cured. Using data from GP practices, hospitals and the Office of National Statistics (which reports information on deaths) in the UK we will be investigating the links between having tuberculosis disease and a patient’s future risk of developing diabetes, pulmonary disease (e.g. asthma or chronic obstructive pulmonary disease), and cardiovascular diseases (like strokes and heart attacks). We will identify people who have had tuberculosis in the past using these health care records and then follow them through time to see if they develop any of these key chronic conditions. Because the datasets in the UK are very large and complete, we will be able to examine whether other factors (including age, sex, smoking status, obesity, ethnicity, or other health conditions) seem to also affect these risks. This will help us identify which patients with tuberculosis might be at the highest risk of future illness and therefore design appropriate screening and other interventions and health care services to help improve their future long-term health. We will also assess the risk of being hospitalised or dying from COVID-19 for people with previous TB disease.
Globally Tuberculosis accounts for more deaths due to infectious disease than any other pathogen; around 1.5 million in 2018. Antimicrobial treatment for TB is highly effective, but may result in long-term consequences for TB survivors considered bacteriologically cured. These include chronic inflammation, insulin resistance, lipid dysregulation, and systemic glucose intolerance [1] which predispose to type 2 diabetes mellitus (DM) and CVD. TB-attributable lung damage may also lead to pulmonary impairment and lifelong respiratory disability. This proposal will improve understanding of the relationship between TB disease and subsequent risks of DM, pulmonary disease and CVD, and identify targets for preventing non-communicable diseases (NCDs) among TB patients. We will also assess COVID-19 hospitalisation and mortality risk for our cohort of post-TB patients.
To address these questions, we will use large routine national datasets to assemble a cohort of over 5,000 patients with a history of TB disease. We will use CPRD primary care datasets, classifying patients using Read codes, utilising general practices in England linked to hospital admissions and mortality data. Specifically, we will determine the extent to which TB disease increases the risk of development of type 2 diabetes mellitus (T2DM), pulmonary disease (asthma, COPD) and specific vascular diseases. We will then assess the extent to which biologic sex, Body Mass Index, HIV, race/ethnicity, and age at time of TB disease modify and mediate the relationships between TB and NCD incidence. Finally, we will explore whether TB clinical characteristics can predict early NCD incidence (first diagnosis of an NCD within 5 years after TB diagnosis) among survivors. We will use Cox’s regression models to examine the incidence of different NCDs, fitting terms for each effect modifier and also describing the patterns of risk within ethnic strata. We will develop a risk score to identify patients at risk of early NCD development.
The primary outcome will be an incident NCD of interest. These will be classified into 3 main groups;
1) Type 2 Diabetes (T2DM)
2) Pulmonary disease (COPD, asthma)
3) Vascular Diseases where atherosclerosis is the predominant aetiology (Ischaemic Stroke [IS], Coronary Artery Disease [CAD], Peripheral Vascular Disease [PVD] and Transient Ischaemic Attack [TIA]).
Each NCD incident event will be defined based on a combination of diagnostic codes (i.e. Read Codes) and prescription data, using methods previously developed and applied in CPRD data[2-5]. Incident events that result in hospitalisation or death will also be included (see section on data linkages requested).
Julia Critchley - Chief Investigator - St George's, University of London
Julia Critchley - Corresponding Applicant - St George's, University of London
Derek Cook - Collaborator - St George's, University of London
Iain Carey - Collaborator - St George's, University of London
Lawrence Phillips - Collaborator - Emory University Medical School
Mary Rhee - Collaborator - Emory University
Matthew Magee - Collaborator - Emory University
Sara Auld - Collaborator - Emory University
Stephen DeWilde - Collaborator - St George's, University of London
Tess Harris - Collaborator - St George's, University of London
Umar Chaudhry - Collaborator - St George's, University of London
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation