Inflammatory arthritis such as rheumatoid arthritis affects over half-a million people in the UK. They occur due to the bodys own defence mechanism i.e. the immune system becoming overactive, and damaging the joints. These conditions are treated with immune-suppressing medicines such as methotrexate and leflunomide that are effective in controlling the arthritis, but, can cause blood, liver or kidney injury. As a result, monitoring blood-tests are performed regularly to identify them early, so that harmful treatment can be discontinued. However, small studies suggest that blood, liver or kidney injury is rare after the first year of treatment. Despite this, regular blood-tests continue for the entire treatment duration, which can be lifelong.
In this study, we will evaluate the utility of long-term monitoring blood-tests in identifying blood, kidney or liver injury due to tablets such as methotrexate, using anonymous information from the Clinical Practice Research Datalink. Data about people with inflammatory arthritis will be extracted, and, prescription and blood test results obtained from the database. We will estimate the proportion of people reducing or discontinuing treatments such as methotrexate due to abnormal blood test results in the second, and each subsequent year of prescription by a GP. We will develop a risk score to predict people likely to experience these side effects after the first year of treatment, so that monitoring can be targeted to those that are at risk.
Background: Methotrexate and leflunomide are first and second-line treatments for autoimmune rheumatic diseases. They cause idiosyncratic haematological, renal, and hepatic toxicities, and, periodic blood-tests are recommended to identify such abnormalities early, so that potentially toxic drugs can be stopped before they cause damage. Small studies suggest that these abnormalities generally occur within first year of treatment and are uncommon in second year. Similarly, while more frequent monitoring tests are recommended for individuals with co-morbidities, old age etc., there are scant data to support this recommendation, and to identify people likely to benefit from closer monitoring.
Objectives:
- Estimate proportion discontinuing methotrexate or leflunomide with an abnormal blood-test result, in each 12-month period of prescription.
- Estimate proportion reducing dose of methotrexate or leflunomide with an abnormal blood-test results, in each 12-month period of prescription.
- Develop risk prediction score to identify those at risk of drug discontinuation due to abnormal blood-test result after 12-month of treatment.
- Develop risk prediction score to identify those at risk of dose reduction due to abnormal blood-test result after 12-month of treatment.
Methods: Data from the Clinical Practice Research Datalink (CPRD) Gold and Aurum will be used. CPRD is an anonymised longitudinal database of UK general practice records, incepted in 1987, and includes data from over 32 million people. It includes information on demographics, lifestyle factors, diagnoses, results of investigations and prescriptions etc. People with autoimmune rheumatic diseases prescribed methotrexate or leflunomide will be ascertained from the time of their first GP prescription, and followed up electronically to estimate the proportion discontinuing or reducing the dose of treatment in each 12-month period in CPRD Gold. Cox-regression will be used to develop a risk prediction score in CPRD Gold. This will be validated in CPRD Aurum excluding any participants who are also in CPRD Gold.
[1] Methotrexate discontinuation
[2] Leflunomide discontinuation
[3] Methotrexate dose reduction
[4] Leflunomide dose reduction
Abhishek Abhishek - Chief Investigator - University of Nottingham
Abhishek Abhishek - Corresponding Applicant - University of Nottingham
Christian Mallen - Collaborator - Keele University
Georgina Nakafero - Collaborator - University of Nottingham
Guruprasad Aithal - Collaborator - University of Nottingham
Maarten Taal - Collaborator - University of Nottingham
Matthew Grainge - Collaborator - University of Nottingham
Michael Doherty - Collaborator - University of Nottingham
Timothy Card - Collaborator - University of Nottingham
Weiya Zhang - Collaborator - University of Nottingham