Due to copyright issues, an electronic copy of the thesis must be ordered from the faculty. For the faculty to have time to process the order, the order must be received by the faculty at the latest 2 days before the public defence. Orders received later than 2 days before the defence will not be processed. After the public defence, please address any inquiries regarding the thesis to the candidate.
Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Professor Nicholas Latimer, University of Sheffield,
- Second opponent: Associate Professor Maiwenn Al, Erasmus University Rotterdam,
- Third member and chair of the evaluation committee: Associate professor Morten Valberg, University of Oslo
Chair of the Defence
Professor Magne Thoresen, University of Oslo
Principal Supervisor
Professor Eline Aas, University of Oslo
Summary
Reimbursement decisions for new cancer treatments often rely on immature survival data from clinical trials in an early stage, which increases the risk of committing resources to treatments that do not provide the expected health benefits.
Reimbursement decisions for new pharmaceuticals, diagnostic tests, and other health technologies are often informed by health economic evaluations. These evaluations estimate the expected health benefits and costs of competing health technologies to help decision makers prioritize those that provide the greatest health benefits for the resources invested. Treatments that aim to improve survival require accurate estimates of life-expectancy in the relevant patient population. However, estimating long-term survival from immature survival data requires a high degree of extrapolation beyond the observed follow-up period, which can lead to substantial uncertainty about the long-term effectiveness and cost-effectiveness of a new treatment.
Additional data collection can reduce uncertainty, and its value can be quantified using value of information methods. This thesis aims to develop accessible and efficient value of information methods to determine the need for collecting survival data with longer follow-up before making a reimbursement decision.
Practical and efficient methods are presented that standardize value of information calculations for collecting survival data from a traditional health economic analysis. The methods are illustrated in a real-world case study drawn from an appraisal of Pembrolizumab plus Axitinib for treating advanced renal cell carcinoma in which the initial decision was informed by immature survival data. Results demonstrate that the methods can be used to determine if additional follow-up is needed before making a reimbursement decision and whether to grant or delay patient access to new health technologies while collecting further data.
Additional information
Contact the research support staff.