Literature DB >> 30543005

Oncology from an HTA and Health Economic Perspective.

Clement Francois1, Junwen Zhou1, Michał Pochopien1, Leila Achour2, Mondher Toumi3.   

Abstract

In this chapter, we will present and discuss the challenges of assessing oncology products from a health economic perspective. We will provide a brief introduction on the need for economic evaluation in health care and focus on cost-effectiveness and comparative aspects of the evaluation of oncology products, which are of paramount interest to HTA decision-making bodies using economic evaluation in their decision-making framework. As the burden of oncology is well-documented, we do not discuss it in detail here. Before we address the specific issue of oncology, we will briefly define the critical aspects of HTA assessment and also define what a cost-effectiveness analysis is and why economic modelling is the most appropriate tool to assess the cost-effectiveness of oncology products. We will touch upon the prices of oncology drugs and the questions that high prices raise regarding funding and availability. We then present an overview of the general structure of an oncology cost-effectiveness model. Usually, this is quite simple, representing response, progression, advanced-stage disease and death. Despite the relative simplicity of these models, some issues may render the evaluation more complex; we will touch upon these in this chapter: Issue with clinical inputs due to the design of randomised clinical trials (e.g. cross-over designs involving a treatment switch) Need for survival extrapolation and limitations of current parametric models Rare conditions with limited economic and comparative evidence available High pace of clinical development Finally, we will conclude with a discussion of the uncertainty around the evaluation of oncology products and the major evolution expected in health economics in oncology.

Entities:  

Keywords:  Cost-effectiveness; Decision-making; Health technology assessment; Oncology drugs

Mesh:

Year:  2019        PMID: 30543005     DOI: 10.1007/978-3-030-01207-6_3

Source DB:  PubMed          Journal:  Recent Results Cancer Res        ISSN: 0080-0015


  1 in total

1.  Impact of limited sample size and follow-up on single event survival extrapolation for health technology assessment: a simulation study.

Authors:  Jaclyn M Beca; Kelvin K W Chan; David M J Naimark; Petros Pechlivanoglou
Journal:  BMC Med Res Methodol       Date:  2021-12-18       Impact factor: 4.615

  1 in total

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