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Personalized medicine and comparative effectiveness research in an era of fixed budgets.

Brown PM - EPMA J (2010)

Bottom Line: For personalized medicine to be widely adopted in clinical practice, stakeholders need evidence of effectiveness, cost effectiveness and financial viability.Comparative effectiveness research (CER) using population based, retrospective data can inform assessments of personalized medicine.Finally, in order to address stakeholder concerns regarding short term financial viability, additional emphasis should be devoted to cost analysis of implementation costs and overall financial impact.

View Article: PubMed Central - PubMed

Affiliation: Lineberger Comprehensive Cancer Center & Institute of Pharmacogenomics and Individualized Therapies, University of North Carolina, Chapel Hill, Chapel Hill, NC USA ; Department of Health Policy & Management, University of North Carolina, 1101e McGavran Greenberg, Chapel Hill, NC 27599 USA.

ABSTRACT
For personalized medicine to be widely adopted in clinical practice, stakeholders need evidence of effectiveness, cost effectiveness and financial viability. Comparative effectiveness research (CER) using population based, retrospective data can inform assessments of personalized medicine. The purpose of this paper is to explore the potential and the limitations of CER. While the analytic methods and data used for CER overcome many of the disadvantages of randomized controlled trials, there are significant barriers, including lack of routinely collected genetic information, patient-reported outcomes and information on new and emerging technologies. Recommendations for using CER include augmenting current data with genetic information, promoting the collection of uniform health outcomes, using value of information analysis to guide development of new technologies, and greater use of decision analysis. Finally, in order to address stakeholder concerns regarding short term financial viability, additional emphasis should be devoted to cost analysis of implementation costs and overall financial impact.

No MeSH data available.


Comparative effectiveness of two drugs
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Fig1: Comparative effectiveness of two drugs

Mentions: At first glance, there would appear to be a conflict between personalized medicine and CER. Whereas the goal of personalized medicine is to produce a treatment tailored for each individual, CER yields global assessments of the average effectiveness of treatments across populations. Since people respond differently to various treatments, the goal should be to find the treatment that is right for them, not the treatment that is right ‘on average’. For instance, consider two drugs (A and B) with average levels of effectiveness of 4 and 5, respectively (Fig. 1). If the treatment decision was based on the average level of effectiveness, the conclusion would be that B should be recommended over A. But because there is variation in the effectiveness, there are some individuals treated with B who did worse than 4, and other individuals treated with A who did better than 5. This raises the possibility that some people might be better off being treated with A, others with B, and looking for one favored treatment ignores the potential benefits from personalizing treatment.Fig. 1


Personalized medicine and comparative effectiveness research in an era of fixed budgets.

Brown PM - EPMA J (2010)

Comparative effectiveness of two drugs
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3405343&req=5

Fig1: Comparative effectiveness of two drugs
Mentions: At first glance, there would appear to be a conflict between personalized medicine and CER. Whereas the goal of personalized medicine is to produce a treatment tailored for each individual, CER yields global assessments of the average effectiveness of treatments across populations. Since people respond differently to various treatments, the goal should be to find the treatment that is right for them, not the treatment that is right ‘on average’. For instance, consider two drugs (A and B) with average levels of effectiveness of 4 and 5, respectively (Fig. 1). If the treatment decision was based on the average level of effectiveness, the conclusion would be that B should be recommended over A. But because there is variation in the effectiveness, there are some individuals treated with B who did worse than 4, and other individuals treated with A who did better than 5. This raises the possibility that some people might be better off being treated with A, others with B, and looking for one favored treatment ignores the potential benefits from personalizing treatment.Fig. 1

Bottom Line: For personalized medicine to be widely adopted in clinical practice, stakeholders need evidence of effectiveness, cost effectiveness and financial viability.Comparative effectiveness research (CER) using population based, retrospective data can inform assessments of personalized medicine.Finally, in order to address stakeholder concerns regarding short term financial viability, additional emphasis should be devoted to cost analysis of implementation costs and overall financial impact.

View Article: PubMed Central - PubMed

Affiliation: Lineberger Comprehensive Cancer Center & Institute of Pharmacogenomics and Individualized Therapies, University of North Carolina, Chapel Hill, Chapel Hill, NC USA ; Department of Health Policy & Management, University of North Carolina, 1101e McGavran Greenberg, Chapel Hill, NC 27599 USA.

ABSTRACT
For personalized medicine to be widely adopted in clinical practice, stakeholders need evidence of effectiveness, cost effectiveness and financial viability. Comparative effectiveness research (CER) using population based, retrospective data can inform assessments of personalized medicine. The purpose of this paper is to explore the potential and the limitations of CER. While the analytic methods and data used for CER overcome many of the disadvantages of randomized controlled trials, there are significant barriers, including lack of routinely collected genetic information, patient-reported outcomes and information on new and emerging technologies. Recommendations for using CER include augmenting current data with genetic information, promoting the collection of uniform health outcomes, using value of information analysis to guide development of new technologies, and greater use of decision analysis. Finally, in order to address stakeholder concerns regarding short term financial viability, additional emphasis should be devoted to cost analysis of implementation costs and overall financial impact.

No MeSH data available.