Evidence map›Paper›PMID 31308725›Full record

ArticlePharmacogenomics and personalized medicine2019

Inconsistency in race and ethnic classification in pharmacogenetics studies and its potential clinical implications.

Frederick Zhang, Joseph Finkelstein

Abstract read
In one paragraph

Article in Pharmacogenomics and personalized medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  9. Online Database of Clinical Algorithms with Race and Ethnicity.medRxiv : the preprint server for health sciences · 2025
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  17. Genes · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Frederick ZhangCenter for Bioinformatics and Data Analytics, Columbia University Irving Medical Center, New York, NY, USA.
Joseph FinkelsteinDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRacial and ethnic categories are frequently used in pharmacogenetics literature to stratify patients; however, these categories can be inconsistent across different studies. To address the ongoing debate on the applicability of traditional concepts of race and ethnicity in the context of precision medicine, we aimed to review the application of current racial and ethnic categories in pharmacogenetics and its potential impact on clinical care.

methodsOne hundred and three total pharmacogenetics papers involving the

resultsThe racial and ethnic categories used in the papers we analyzed were highly heterogeneous. In total, we found 66 different racial and ethnic categories used which fall under the NIH race category "White", 47 different racial and ethnic categories for "Asian", and 62 different categories for "Black". The number of categories used varied widely based on country of origin: Japan used the highest number of different categories for "White" with 17, Malaysia used the highest number for "Asian" with 24, and the US used the highest number for "Black" with 28. Significant variation in allele frequency between different ethnic subgroups was identified within 3 major continental racial categories.

conclusionOur analysis showed that racial and ethnic classification is highly inconsistent across different papers as well as between different countries. Evidence-based consensus is necessary for optimal use of self-identified race as well as geographical ancestry in pharmacogenetics. Common taxonomy of geographical ancestry which reflects specifics of particular countries and is accepted by the entire scientific community can facilitate reproducible pharmacogenetic research and clinical implementation of its results.

Indexed as

drug responsivenessethnic differencespharmacogeneticssingle nucleotide polymorphism

Identifiers

PMID31308725
PMCPMC6612983

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.