Authors' objectives: Background: This study will develop better methods for making recommendations for when people should take long-term drugs to prevent future heart disease/stroke or fracture due to osteoporosis (bone thinning). These recommendations are informed by two different types of mathematical model that are used to help predict what will happen in the future. Guideline developers use economic models to identify groups of patients who are likely to benefit from treatment. Doctors use risk-prediction models to identify who should be offered treatment. For example, based on an economic model, the NICE guideline on high cholesterol recommends only treating people with more than a 1 in 10 chance of heart attack/stroke in the next 10 years. Doctors work out individual patient's future risk of a heart attack/stroke by entering information about them into a risk-prediction calculator and only offer statin treatment to patients at high risk. The design of these models therefore directly affects the treatments which doctors recommend to patients. These treatments are taken long-term, often for the rest of someone s life. The accuracy of these two types of mathematical model is therefore important because large numbers of people are potentially affected by decisions based on them. However, risk prediction tools and economic models may not be accurate for people with multiple health conditions (multimorbidity), because this group may die from these other conditions before they can develop heart disease or stroke or have a fracture. Economic models also do not account for the burden of taking a medicine for many years, which really matters to some patients and which may outweigh the relatively small benefit of preventive drugs. Overall aim: To improve the evidence generated from risk prediction and economic models to better inform decision-making for selecting medicines to prevent heart disease/stroke and fracture in people with multimorbidity. Design and methods: Study 1 will use information from general practice records to develop two new tools to predict the risk of developing heart disease/stroke and fracture in people with multimorbidity who do not have either condition. We will carry out initial checks of the accuracy of these tools, and compare them to risk prediction tools already being used in the NHS. Study 2 will use a specially designed survey to find out the effect on quality of life from taking different long-term medicines. Some people find taking medicines a significant burden but this is not taken into account in economic models at the moment. Study 3 will use the results from the first two studies to examine the expected benefit and value for money of statins to prevent heart disease/stroke and bisphosphonates to prevent fracture in people with multimorbidity and/or limited life expectancy. Public involvement: Interviews with patients and discussion with an NHS public partners group informed study design. Two public partners have agreed to join the advisory group, have commented on the proposal, and will contribute to the study 2 survey design and the interpretation of the findings. Dissemination: We will use a range of methods to ensure that all interested people (eg academics, clinicians, guideline developers, the public) get to know about the results, including the final report to NIHR, academic papers, clinical and public summaries, and the offer of workshops to key groups such as NICE.

Project Status: Ongoing

URL for project: http://www.nets.nihr.ac.uk/projects/hsdr/151222

Anticipated Publish Date: 2021

English language abstract: An English language summary is available

Publication Type: Not Assigned

Country: England, United Kingdom

Organisation Name: NIHR Health Services and Delivery Research programme

Contact Address: NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK

Contact Name: journals.library@nihr.ac.uk

Contact Email: journals.library@nihr.ac.uk

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