University of Edinburgh

HDR UK

DL_2024_034

Before doctors can prescribe medicines, clinical trials must show that they are safe and that they work. However, trials last for a short period of time, and not everyone can take part in them. Thus, we still have unanswered questions about how safe and effective these medications are in real life. This research will examine conventional and newer medications used in rheumatology. This will include medicines for inflammatory diseases, like rheumatoid arthritis and lupus. These diseases occur when the body's immune system overreacts, causing swelling and pain. It will also include medicines used in diseases that affect the bones, like osteoporosis and rickets. We will study the benefits and side effects of medications over a longer time period compared to trials and consider groups often excluded from trials, such as those with more medical conditions. We will also examine differences in clinical factors and patient characteristics to see if these can help with treatment decisions. This is important because in many cases we cannot predict which medication will work for a patient before starting the treatment. We will use Scotland’s excellent healthcare information system to create the necessary linked dataset. It will have data on people seen in rheumatology clinics across Scotland. It will combine data on deaths, hospital admissions, cancer registrations, lab test results and medical imaging with data on prescriptions. Public Health Scotland will link the datasets and remove all personal identifiers. We will then analyse the data inside the National Safe Haven, which is a safe computing environment owned by Public Health Scotland. We will first process the data to clean it and make it ready for research. Then, we will use statistical methods to look at differences in outcomes by drug and clinical factors. This research can address safety concerns for newer medications. It can reduce the number of people getting harmful side effects. It can increase the number of people eligible for certain medications. It can inform treatment strategies and help identify who might end-up with substantial disability long-term.

Biologic and targeted synthetic medicines (henceforth ‘advanced treatments’) are the result of recent advancements in biomedical research and work by targeting very specific biological functions in our body (e.g. blocking a protein of the immune system that is causing it to be overactive). In rheumatology, several advanced treatments have become available over the last two decades for people with Immune-Mediated Inflammatory Diseases (IMIDs), such as rheumatoid arthritis and lupus, when conventional treatments are not effective in controlling their disease symptoms. More recently, advanced treatments have also been introduced for metabolic bone diseases like severe osteoporosis and X-linked hypophosphataemic rickets, a rare genetic disorder that causes bone deformities. It is likely that the use of advanced treatments will increase as new medicines are developed and licensed for clinical use, with the global biologics market projected to grow by 9.2% in the period 2022-2027. This project will create a linked dataset of national data and use it to study the real-world safety and effectiveness of existing and new medicines used to treat people with IMIDs or metabolic bone diseases across Scotland. We will also use this dataset to study natural history of disease, and drug use trajectories, and to construct clinical predictive models of response to treatment. Using the proposed “real-world” data resource, our research will add to the available information on the safety and effectiveness of medications prescribed in rheumatology practice. It can address safety concerns for newer medications, where rare but important side effects could have been missed by clinical trials, and for patient subgroups that are typically excluded in trials (e.g. pregnant women, aged 75+). It can reduce the number of people getting harmful side effects, for instance by avoiding burdensome medications in people who have pre-existing medical conditions or who are already taking many medications. It can increase the number of people eligible for certain medications, by demonstrating their effectiveness when used “off-label” (i.e. in treating conditions they are not approved for). We will design our research studies to meet the requirements of the National Institute for Health and Care Excellence (NICE—the national governing body who evaluates and regulates the use of medicines in the UK), so that findings can be used to update prescribing recommendations and guidelines. Through application of risk prediction methodologies, our research can help identify who is more likely to develop long-term disability or loss of function and inform medical needs and research priorities on the basis of long-term outcomes (e.g. joint deformities) rather than short-term disease activity measures which are typically used in clinical trials. It can also help predict who will show insufficient response to first-line treatments, and thus lead to more personalised treatment decisions, in cases where many treatments are available, but it is not possible to tell which treatment will work for each patient prior to treatment. For instance, a large proportion of people with rheumatoid arthritis end up trying several medications before finding one that works. This “trial-and-error” period is associated with (sometimes permanent) joint damage, increased pain, and frustration.

Public Health Research

14/01/2025

De-Personalised

TRE