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Estimating the impact of different approaches to the analysis of time-to-event and longitudinal data on modelled cost-effectiveness.
Proposal
2069
Title of Proposed Research
Estimating the impact of different approaches to the analysis of time-to-event and longitudinal data on modelled cost-effectiveness.
Lead Researcher
Ben Kearns
Affiliation
School of Health and Related Research (ScHARR), The University of Sheffield
Funding Source
NIHR Doctoral Fellowship (awarded to Ben Kearns).
Potential Conflicts of Interest
Data Sharing Agreement Date
30 August 2018
Lay Summary
A health technology is any technology that can be used to improve peoples' health. Examples include screening programmes, the use of drugs to treat a disease, and different methods for performing surgery. Within England, There are more health technologies than the National Health Service (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. It seeks to answer the question: does the technology represent value for money? In other words, is it cost-effective? To answer this question we need to know about two outcomes. Firstly, what is the cost to the NHS of using this health technology? This includes both the cost of the technology, and any longer-term costs, such as monitoring or treating adverse events. Secondly, what are the benefits to the patient? For example, for a new cancer drug, patient benefits could be that it keeps them alive for longer, and/or that it improves their health-related quality of life. Normally, for health technology assessments we want to know about these outcomes for patients' entire lifetimes. 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. This study shall compare different methods for predicting long-term patient benefits, and the impact of these on estimates of cost-effectiveness. It shall use as a case-study a trial of a cancer drug (Cyramza) for people with lung cancer. Within the United Kingdom, the National Institute for Health and Care Excellence (NICE) previously decided that Cyramza was not cost-effective. During the decision-making process it was noted that there was uncertainty in the long-term estimates of patient outcomes. This study shall look at different methods for estimating long-term outcomes, and the impact of these on estimates of cost-effectiveness.This study is part of a wider project entitled “Good practice guidance for the prediction of future outcomes in health technology assessment” (https://t.co/NwJ9mRtczH). This project has active public involvement to help with interpretation and communication of the study findings.
Study Data Provided
[{ "PostingID": 4540, "Title": "LILLY-I4T-MC-JVBA", "Description": "A Randomized, Double-Blind, Phase 3 Study of Docetaxel and Ramucirumab versus Docetaxel and Placebo in the Treatment of Stage IV Non-Small Cell Lung Cancer Following Disease Progression after One Prior Platinum-Based Therapy (REVEL)" }]
Statistical Analysis Plan
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