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The economic value of personalized medicine tests: what we know and what we need to know.

ABSTRACT: There is uncertainty about when personalized medicine tests provide economic value. We assessed evidence on the economic value of personalized medicine tests and gaps in the evidence base.We created a unique evidence base by linking data on published cost-utility analyses from the Tufts Cost-Effectiveness Analysis Registry with data measuring test characteristics and reflecting where value analyses may be most needed: (i) tests currently available or in advanced development, (ii) tests for drugs with Food and Drug Administration labels with genetic information, (iii) tests with demonstrated or likely clinical utility, (iv) tests for conditions with high mortality, and (v) tests for conditions with high expenditures.We identified 59 cost-utility analyses studies that examined personalized medicine tests (1998-2011). A majority (72%) of the cost/quality-adjusted life year ratios indicate that testing provides better health although at higher cost, with almost half of the ratios falling below $50,000 per quality-adjusted life year gained. One-fifth of the results indicate that tests may save money.Many personalized medicine tests have been found to be relatively cost-effective, although fewer have been found to be cost saving, and many available or emerging medicine tests have not been evaluated. More evidence on value will be needed to inform decision making and assessment of genomic priorities.

SUBMITTER: Phillips KA

PROVIDER: S-EPMC3949119 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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The economic value of personalized medicine tests: what we know and what we need to know.

Phillips Kathryn A KA Ann Sakowski Julie J Trosman Julia J Douglas Michael P MP Liang Su-Ying SY Neumann Peter P

Genetics in medicine : official journal of the American College of Medical Genetics 20131017 3

<h4>Purpose</h4>There is uncertainty about when personalized medicine tests provide economic value. We assessed evidence on the economic value of personalized medicine tests and gaps in the evidence base.<h4>Methods</h4>We created a unique evidence base by linking data on published cost-utility analyses from the Tufts Cost-Effectiveness Analysis Registry with data measuring test characteristics and reflecting where value analyses may be most needed: (i) tests currently available or in advanced d ...[more]

PMID: 24232413

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Project description:BackgroundClinical care is moving from a "one size fits all" approach to a setting in which treatment decisions are based on individual treatment response, needs, preferences, and risk. Research into personalized treatment strategies aims to discover currently unknown markers that identify individuals who would benefit from treatments that are nonoptimal at the population level. Before investing in research to identify these markers, it is important to assess whether such research has the potential to generate value. Thus, this article aims to develop a framework to prioritize research into the development of new personalized treatment strategies by creating a set of measures that assess the value of personalizing care based on a set of unknown patient characteristics.MethodsGeneralizing ideas from the value of heterogeneity framework, we demonstrate 3 measures that assess the value of developing personalized treatment strategies. The first measure identifies the potential value of personalizing medicine within a given disease area. The next 2 measures highlight specific research priorities and subgroup structures that would lead to improved patient outcomes from the personalization of treatment decisions.ResultsWe graphically present the 3 measures to perform sensitivity analyses around the key drivers of value, in particular, the correlation between the individual treatment benefits across the available treatment options. We illustrate these 3 measures using a previously published decision model and discuss how they can direct research in personalized medicine.ConclusionWe discuss 3 measures that form the basis of a novel framework to prioritize research into novel personalized treatment strategies. Our novel framework ensures that research targets personalized treatment strategies that have high potential to improve patient outcomes and health system efficiency.HighlightsIt is important to undertake research prioritization before conducting any research that aims to discover novel methods (e.g., biomarkers) for personalizing treatment.The value of unexplained heterogeneity can highlight disease areas in which personalizing treatment can be valuable and determine key priorities within that area.These priorities can be determined under assumptions of the magnitude of the individual-level treatment effect, which we explore in sensitivity analyses.

Dataset Information

The economic value of personalized medicine tests: what we know and what we need to know.

Publications

The economic value of personalized medicine tests: what we know and what we need to know.

Similar Datasets

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