Literature DB >> 20515285

When do new biomarkers make economic sense?

Mitchell G Scott1.   

Abstract

Cost-effectiveness and cost-utility studies are commonly used to make payment decisions for new drugs and expensive interventions. Such studies are relatively rare for evaluating the cost-utility of clinical laboratory tests. As medical costs continue to increase in the setting of decreased resources it is likely that new biomarkers may increasingly be examined with respect to their economic benefits in addition to clinical utility. This will represent an additional hurdle for routine use of new biomarkers. Before reaching the final economic hurdle new biomarkers will still need to demonstrate clinical usefulness. Thus a new biomarker will never make economic sense if it is not clinically useful. Once diagnostic accuracy and potential clinical usefulness is established there are several types of economic studies that new biomarkers may undergo. The most common of these are cost-utility studies which estimate the ratio between the cost of an intervention or test and the benefit it produces in the number of years gained in full health. The quantity used most often to describe this is amount of money per quality adjusted life year (QALY) gained. The threshold for being considered cost-effective is generally USD 50,000 per QALY gained. Examples of biomarkers that have been subjected to economic analyses will be provided.

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Year:  2010        PMID: 20515285     DOI: 10.3109/00365513.2010.493411

Source DB:  PubMed          Journal:  Scand J Clin Lab Invest Suppl        ISSN: 0085-591X


  8 in total

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Authors:  Jennifer L Wilson; Russ B Altman
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Review 4.  Gene Expression Detection Assay for Cancer Clinical Use.

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6.  Diagnostic model for pancreatic cancer using a multi-biomarker panel.

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Journal:  Ann Surg Treat Res       Date:  2021-02-26       Impact factor: 1.859

7.  Stratified medicine and reimbursement issues.

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8.  Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges.

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Journal:  Clin Proteomics       Date:  2013-10-02       Impact factor: 3.988

  8 in total

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