Award Title: Investigating methods of incorporating Real-World Data in Health Technology Assessment (HTA) Decision-Making: application in Rheumatoid Arthritis
Funder: Department of Health and Social Care

Abstract: Research question This project will determine how statistical methods can be developed to incorporate evidence from non-randomised studies into a health technology assessment (HTA). In particular, how to combine data from randomised controlled trials (RCT) with real-world data (RWD) to improve the appropriateness of clinical effectiveness estimates. The evaluation of biologic treatments for patients with rheumatoid arthritis (RA) will be used as a case-study. Background A HTA seeks to evaluate a medical intervention by synthesising evidence regarding its safety, clinical effectiveness, and cost effectiveness. The clinical effectiveness evidence is largely based on RCT data. This evidence is reliable because RCTs have high internal validity. However, findings from RCTs are not always generalizable to the patient population. RWD refers to data collected from sources other than RCTs (e.g. patient-registries or single-arm trials). RWD are more reflective of observations seen in everyday clinical practice, but are susceptible to bias. HTA agencies have acknowledged potential advantages in combining RCT data with RWD, and recommend further research into methodological development for this purpose. Aims	To identify and develop meta-analytic methods which can be used to synthesise clinical effectiveness data obtained from RCTs and RWD, whilst accounting for bias inherent in RWD. 	To evaluate the methods under different conditions, with a focus on individual participant data (IPD) availability, and the number of RCTs in the synthesis. 	To investigate how the methods can be developed to adjust for bias in clinical effectiveness estimates recorded over time. 	To investigate how the methods impact on decision model estimates and conclusions in HTAs.Methods	I will update a systematic literature review to identify existing meta-analytic methods combining RCT data with RWD. I will then develop and apply the methods to combine IPD from RCTs and single-arm studies in RA. I will also apply the methods to data from the Clinical Practice Research Datalink. 	I will perform a simulation study to evaluate methods by applying them to datasets generated under conditions where the number of studies with available IPD is varied, the number of RCTs is varied. 	I will develop and apply bias-adjustment methods (e.g. multivariable regression) to update Health Assessment Questionnaire estimates recorded over time, using data from the British School of Rheumatology - Biologics Register. 	I will update a published HTA by implementing the methods to obtain an adjusted pooled clinical effectiveness estimate, and re-run the decision model to calculate an updated incremental cost effectiveness ratio estimate.Anticipated impact and dissemination The research undertaken in this project will be detailed in articles submitted for publication to relevant academic journals. I will communicate my research findings via a public and patient advisory group. I will present my work at international conferences attended by expert researchers. The work will impact other researchers who are interested in methodological development and evidence synthesis, and aid analysts, performing future HTAs, in a more robust synthesis of diverse sources of evidence. Ultimately, it will enable HTA agencies to make better decisions regarding treatments, improving the healthcare-quality experienced by patients in the National Health Service.

Lay Abstract: Background to the research In research, the best way to test whether a treatment works is to do a clinical trial. This usually involves randomly giving a patient one treatment and comparing it with another treatment. This is called a 'randomised controlled trial'. However, at least half of patients are not allowed to be in clinical trials. This is because researchers want participants to be very similar to one another so that they can test the treatment properly. Patients might be excluded if they cannot consent for themselves (e.g. due to disability). They might also be excluded because they have other diseases or are very sick. These people still need to be treated when they are seen by a doctor. It can be difficult for doctors to know what to prescribe for them because they don't know what works. As a solution, researchers will often look at information from everyday practice to look at people who cannot be in clinical trials. This might include information from GP surgeries, walk-in clinics or hospital appointments. We call this 'real-world data'. It includes seeing whether patients get better when they are prescribed a treatment by looking at their measurements. However, real-world evidence has weaknesses over clinical trials because patients are not selected randomly so there might be other reasons that they are getting better or worse. For some treatments, there may be a lot of evidence from clinical trials and real-world data. This evidence is usually summarised in a document called a 'Health Technology Assessment' (HTA). The Government's National Institute for Health and Care Excellence (NICE) relies on these HTAs to work out if a treatment is of good value. They then make recommendations to the National Health Service on what treatments to buy. They have said that researchers should look at methods of combining information from clinical trials and real-world data so that they get the best picture about what works. Aims The aims of my study are:	To build-on current methods for combining information from clinical trials and real-world data. 	To test these methods in the real-world setting. 	To adapt the methods to assess information from real-world data 	To look into how the different methods affect conclusions in HTAs.Methods To achieve the aims:	I will look at previous research on methods of combining information from clinical trials and real-world data. I will then apply the methods to see what treatments work for patients with rheumatoid arthritis. 	I will use a computer program to create artificial (made-up) measurements to see how the methods perform in different situations. In particular, when there are not many clinical trials about the treatment. 	I will add to the methods and apply them to information recorded over time using the Health Assessment Questionnaire from a patient registry. 	I will see whether using the new methods improves the estimates of the treatment's value. I will update a previous HTA that assesses treatments for rheumatoid arthritis and see if the conclusions change.Patient involvement A group of patients with rheumatoid arthritis will help me with this project. I will ask them to tell me about outcomes that are important to them. I will also talk about the work I have done and how it will impact them as service users. Dissemination I will write up my work in research articles so that other researchers have a chance to look at my work. I will tell people about my study using social media. I will also go to conferences around the world to tell people about my findings.

Research Activity Codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health Categories: INFLAMMATORY AND IMMUNE SYSTEM