Dataset Information

The future of warfarin pharmacogenetics in under-represented minority groups.

ABSTRACT: Genotype-based dosing recommendations are provided in the US FDA-approved warfarin labeling. However, data that informed these recommendations were from predominately Caucasian populations. Studies show that variants contributing to warfarin dose requirements in Caucasians provide similar contributions to dose requirements in US Hispanics, but significantly lesser contributions in African-Americans. Further data demonstrate that variants occurring commonly in individuals of African ancestry, but rarely in other racial groups, significantly influence dose requirements in African-Americans. These data suggest that it is important to consider variants specific for African-Americans when implementing genotype-guided warfarin dosing in this population.

SUBMITTER: Cavallari LH

PROVIDER: S-EPMC3463230 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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The future of warfarin pharmacogenetics in under-represented minority groups.

Cavallari Larisa H LH Perera Minoli A MA

Future cardiology 20120701 4

Genotype-based dosing recommendations are provided in the US FDA-approved warfarin labeling. However, data that informed these recommendations were from predominately Caucasian populations. Studies show that variants contributing to warfarin dose requirements in Caucasians provide similar contributions to dose requirements in US Hispanics, but significantly lesser contributions in African-Americans. Further data demonstrate that variants occurring commonly in individuals of African ancestry, but ...[more]

PMID: 22871196

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Project description:BackgroundIn varied educational settings, narrative evaluations have revealed systematic and deleterious differences in language describing women and those underrepresented in their fields. In medicine, limited qualitative studies show differences in narrative language by gender and under-represented minority (URM) status.ObjectiveTo identify and enumerate text descriptors in a database of medical student evaluations using natural language processing, and identify differences by gender and URM status in descriptions.DesignAn observational study of core clerkship evaluations of third-year medical students, including data on student gender, URM status, clerkship grade, and specialty.ParticipantsA total of 87,922 clerkship evaluations from core clinical rotations at two medical schools in different geographic areas.Main measuresWe employed natural language processing to identify differences in the text of evaluations for women compared to men and for URM compared to non-URM students.Key resultsWe found that of the ten most common words, such as "energetic" and "dependable," none differed by gender or URM status. Of the 37 words that differed by gender, 62% represented personal attributes, such as "lovely" appearing more frequently in evaluations of women (p < 0.001), while 19% represented competency-related behaviors, such as "scientific" appearing more frequently in evaluations of men (p < 0.001). Of the 53 words that differed by URM status, 30% represented personal attributes, such as "pleasant" appearing more frequently in evaluations of URM students (p < 0.001), and 28% represented competency-related behaviors, such as "knowledgeable" appearing more frequently in evaluations of non-URM students (p < 0.001).ConclusionsMany words and phrases reflected students' personal attributes rather than competency-related behaviors, suggesting a gap in implementing competency-based evaluation of students. We observed a significant difference in narrative evaluations associated with gender and URM status, even among students receiving the same grade. This finding raises concern for implicit bias in narrative evaluation, consistent with prior studies, and suggests opportunities for improvement.

Dataset Information

The future of warfarin pharmacogenetics in under-represented minority groups.

Publications

The future of warfarin pharmacogenetics in under-represented minority groups.

Similar Datasets

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