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Implementation of comparative effectiveness research in personalized medicine applications in oncology: current and future perspectives

Authors IJzerman M, Manca A, Keizer J, Ramsey S

Received 11 July 2015

Accepted for publication 20 August 2015

Published 26 November 2015 Volume 2015:5 Pages 65—72


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Professor Matthew Maciejewski

Maarten J IJzerman,1,3 Andrea Manca,2,3 Julia Keizer,1 Scott D Ramsey4

1Department of Health Technology and Services Research, University of Twente, Enschede, the Netherlands; 2Centre for Health Economics, University of York, York, UK; 3Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg, 4Fred Hutchinson Cancer Research Center, Seattle, WA, USA

Abstract: Personalized medicine (PM) or precision medicine has been defined as an innovative approach that takes into account individual differences in people's genes, environments, and lifestyles in prevention and treatment of disease. In PM, genomic information may contribute to the molecular understanding of disease, to optimize preventive health care strategies, and to fit the best drug therapies to the patient's individual characteristics. Evidence development in the era of genomic medicine is extremely challenging due to a number of factors. These include the rapid technological innovation in molecular diagnostics and targeted drug discoveries, and hence the large number of mutations and multiple ways these may influence treatment decisions. Although the evidence base for PM is evolving rapidly, the main question to be explored in this article is whether existing evidence is also fit for comparative effectiveness research (CER). As a starting point, this paper therefore reflects on the evidence required for CER and the evidence gaps preventing decisions on market access and coverage. The paper then discusses challenges and potential barriers for applying a CER paradigm to PM, identifies common methodologies for designing clinical trials in PM, discusses various approaches for analyzing clinical trials to infer from population to individual level, and presents an example of a clinical trial in PM (The RxPONDER TRIAL) demonstrating good practice. The paper concludes with a future perspective, including modeling approaches for evidence synthesis.

Keywords: personalized medicine, precision medicine, comparative effectiveness research, health technology assessment, oncology, genomics

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