Literature DB >> 7674318

Potential impact of genetic testing on cancer prevention trials, using breast cancer as an example.

S G Baker1, L S Freedman.   

Abstract

Using breast cancer as an example, we explored the potential impact that a highly predictive genetic test could have on the design and analysis of cancer prevention trials. We discuss three situations in this article: 1) trials that are in progress when the genetic test first becomes available as a research tool but is not available for general use, 2) trials in progress when the genetic test becomes generally available to the public, and 3) trials that begin after the test becomes generally available. We have concluded that the availability of a highly predictive genetic test will provide impediments to prevention trials in the form of increased noncompliance and also will provide opportunities in the form of new trials that include only persons at very high risk of developing cancer. Such trial designs could, under favorable circumstances, substantially reduce the size, duration, and cost of cancer prevention trials. The availability of a highly predictive genetic test will make the discovery of effective interventions even more urgent, and the randomized trial will still provide the most reliable method of evaluating prevention strategies.

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Year:  1995        PMID: 7674318     DOI: 10.1093/jnci/87.15.1137

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  4 in total

1.  Designing a randomized clinical trial to evaluate personalized medicine: a new approach based on risk prediction.

Authors:  Stuart G Baker; Daniel J Sargent
Journal:  J Natl Cancer Inst       Date:  2010-11-01       Impact factor: 13.506

2.  Evaluating surrogate endpoints, prognostic markers, and predictive markers: Some simple themes.

Authors:  Stuart G Baker; Barnett S Kramer
Journal:  Clin Trials       Date:  2014-11-10       Impact factor: 2.486

3.  Biomarker evaluation in randomized trials: addressing different research questions.

Authors:  Stuart G Baker
Journal:  Stat Med       Date:  2014-10-15       Impact factor: 2.373

4.  The fallacy of enrolling only high-risk subjects in cancer prevention trials: is there a "free lunch"?

Authors:  Stuart G Baker; Barnett S Kramer; Donald Corle
Journal:  BMC Med Res Methodol       Date:  2004-10-04       Impact factor: 4.615

  4 in total

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