Literature DB >> 12881555

Genetics. FDA races in wrong direction.

Susanne B Haga1, J Craig Venter.   

Abstract

Despite recent genetic evidence and the promise of individualized medicine, there is a continuing interest in using self-identified categories of race and ethnicity as variables in scientific and medical research. The U.S. Food and Drug Administration recently proposed a standardized approach for the collection of race and ethnicity data in clinical trials. We believe that this move fails to acknowledge new scientific data and recommend that relevant data from individuals be collected and used rather than broad group statistics. We also encourage that increased funding be committed to this important issue.

Mesh:

Year:  2003        PMID: 12881555     DOI: 10.1126/science.1087004

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  6 in total

1.  Characterization of clinical study populations by race and ethnicity in biomedical literature.

Authors:  Priyanka Kanakamedala; Susanne B Haga
Journal:  Ethn Dis       Date:  2012       Impact factor: 1.847

2.  Genetic structure, self-identified race/ethnicity, and confounding in case-control association studies.

Authors:  Hua Tang; Tom Quertermous; Beatriz Rodriguez; Sharon L R Kardia; Xiaofeng Zhu; Andrew Brown; James S Pankow; Michael A Province; Steven C Hunt; Eric Boerwinkle; Nicholas J Schork; Neil J Risch
Journal:  Am J Hum Genet       Date:  2004-12-29       Impact factor: 11.025

3.  Epidemiologic analysis of racial/ethnic disparities: some fundamental issues and a cautionary example.

Authors:  Jay S Kaufman
Journal:  Soc Sci Med       Date:  2008-01-14       Impact factor: 4.634

4.  Ethical concerns related to developing pharmacogenomic treatment strategies for addiction.

Authors:  Alexandra E Shields
Journal:  Addict Sci Clin Pract       Date:  2011-07

5.  Geography and genography: prediction of continental origin using randomly selected single nucleotide polymorphisms.

Authors:  Dominic J Allocco; Qing Song; Gary H Gibbons; Marco F Ramoni; Isaac S Kohane
Journal:  BMC Genomics       Date:  2007-03-10       Impact factor: 3.969

6.  Comparison of Genetic and Self-Identified Ancestry in Modeling Intracerebral Hemorrhage Risk.

Authors:  Sandro Marini; Umme K Lena; Katherine M Crawford; Charles J Moomaw; Fernando D Testai; Steven J Kittner; Michael L James; Daniel Woo; Carl D Langefeld; Jonathan Rosand; Christopher D Anderson
Journal:  Front Neurol       Date:  2018-07-06       Impact factor: 4.003

  6 in total

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