Title: Good practice guidance for the prediction of future outcomes in health technology assessment.
Funder: Department of Health and Social Care

Abstract: Background Limited healthcare budgets mean that not all clinically effective health technologies can be funded. Funding decisions can be based on cost-effectiveness; does the health technology represent value for money? Health technology assessments (HTAs) are conducted to establish the clinical-effectiveness and cost-effectiveness of health technologies, with the aim to inform decisions about funding. Many HTAs require evidence about the lifetime costs and health outcomes associated with the use of a health technology. However, often the evidence base does not cover patients' lifetimes. Because of this, methods for extrapolating evidence are required. Previous research has highlighted that: (1) different approaches to extrapolation can have a marked impact on cost-effectiveness results - and hence funding decisions - and (2) existing approaches are inconsistent, with limited use of advanced (and possibly more appropriate) statistical methods. Hence, there is a need for good-practice guidance to assist with producing extrapolations based on appropriate statistical methodology that take into account the types of data and research questions encountered within HTA. This guidance shall also consider time-series methods, which have the explicit objective of producing extrapolations and estimating their uncertainty. There is an opportunity to consider how time series methods may be combined with existing methods for producing extrapolations.Aims The main research question to be answered by this fellowship is What are appropriate methods for predicting future outcomes in health technology assessments? To answer this question, the fellowship has the following two aims:Identify and develop extrapolation (forecasting) methods that may be used within the context of health technology assessment.Develop a methodological framework that will help to identify good practice for performing extrapolations. Plan of investigation The following research methods shall be considered:How to produce extrapolations for longitudinal data.How to produce extrapolations for time to event data.How to jointly extrapolate correlated data (which may be longitudinal, time to event, or both).How to identify and estimate treatment effects that vary over time. How to incorporate structural uncertainty The plan of investigation is as follows: 1) Prioritise the order in which the research methods are considered. A prioritisation event shall be held, and shall include representatives from the public, academia, and decision-makers. 2) Reviews of the existing literature. For each of the research methods two literature reviews shall be considered. The first shall be a comprehensive review to identify potential methods that may be used. The second review shall be to identify current applications of the research methods in a HTA context. This shall be an update of an existing MRC review. 3) Application of methods to case-studies. At least two case-studies (in the areas of depression and prostate cancer) shall be used to establish the strengths and limitations of the identified methods. Patient-level data shall be used. 4) Production of good-practice guidelines. The guidance shall include a summary of the available statistical methods and how to choose between them. 5) Dissemination of results. Dissemination shall be achieved via open access peer-reviewed publications, lay summaries, presentations at scientific conferences and university seminars. A dissemination workshop shall also be held. If appropriate, software code and a short course shall be produced.Potential benefits to patients and the NHS The proposed research would lead to patient benefits as more accurate predictions of the future cost-effectiveness of health technologies would improve decision-making about how best to allocate a scarce healthcare budget. This improved decision making would also benefit NHS commissioners and providers. It is also anticipated that any methodological development would have benefits to the wider statistical community and to practitioners in other fields (such as public health) for which producing extrapolations are important.

Lay abstract: Aim of the research: The overall aim of this project is to produce guidance on good practice methods to help people make predictions of future outcomes to use in health technology assessment. Background and potential benefits to patients: A health technology is any technology that can be used to improve people's health. Examples include screening programmes, the use of drugs to treat a disease, and different methods for performing surgery. There are more health technologies than the NHS can afford to pay for. Health technology assessment is used to help make decisions about if the NHS should pay for a health technology. In other words, does it represent value for money? To answer this question we need to know about two outcomes: (1) What is the cost to the NHS of using this health technology? (2) What are the benefits to the patient? For example, for a new cancer drug, patient benefits could be that it keeps them alive longer and that it improves their quality of life. Normally, for health technology assessments we want to know about these outcomes for a patient's entire lifetime. However, we often only know about these outcomes for a limited period of time. Hence we often need to predict what these outcomes will be in the future. Improved predictions about future outcomes will help to make sure that the NHS gets the best value for the money it spends. This will in turn help to improve outcomes for people treated by the NHS. Plan of investigation: This work will look at the different methods that we can use to predict the future. There are a number of examples in health technology assessment where these different methods can produce very different predictions. For example, a cancer drug it was predicted that a new drug increased average survival by either two or seven months, depending on the method used. Previous work has shown that existing approaches to creating predictions are inconsistent and usually not of a high standard. Because of this, there is a need for good practice guidance. This guidance would help people to create better predictions of the future.The work shall last for three years, starting in January 2017. There are different types of predictions about the future that are needed. These require different prediction methods. For example, when predicting future survival we need to use different prediction methods to if we are predicting future quality of life. These research methods shall be presented and discussed during a prioritisation event at the start of the work. This event shall prioritise the order in which the prediction methods will be considered. For each prediction method, reviews of health technology assessment shall be performed to identify how often they are being used. The methods shall be tested in at least two case-studies, including one in cancer and one in mental health. The results shall be used to create, good practice guidance. This guidance shall be discussed at a consultation event, which will give people the chance to have their say on the guidance. The guidance shall cover topics such as: (1) What different prediction methods are available? (2) How do we choose between these methods? (3) How do we communicate the uncertainty in our results? Patient and public involvement: This work has been discussed with patients and members of the public during a consultation workshop. We discussed how to involve patients and the public in the work, including the training required. We also discussed and improved this Plain English Summary. When the work starts, a patient and public advisory panel of about ten members shall be established. This shall include patients for the clinical areas considered, along with members of the public. This advisory panel shall attend the prioritisation event, help produce annual Plain English updates of the projects, and help with dissemination of the project results. Dissemination: Findings from this work shall be communicated to patients and the public with the help of the patient and public advisory panel. A website will be set-up, which will provide details about the work, including a Plain English summary of the work each year. The consultation event to discuss the work shall be open to patients and members of the public, and will allow them to provide comments on the guidance. This consultation event shall also include other people involved in health technology assessment. Their involvement, along with talks at conferences and journal articles, shall help to improve practice in health technology assessment.

Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: CANCER AND NEOPLASMS