Evidence map›Paper›PMID 41707036›Full record

ArticleClinical and translational science2026

A Framework to Quantify Disparities in Pharmacogenomic Treatment Concordance and Drug Response Outcomes.

Ilia Rattsev, James M Stevenson, Casey Overby Taylor

Abstract read
In one paragraph

Article in Clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Ilia RattsevInstitute for Computational Medicine, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0001-6284-3204
James M StevensonDivision of Clinical Pharmacology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0003-1640-1135
Casey Overby TaylorInstitute for Computational Medicine, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0001-9302-5968

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical PGx practice guidelines (PGx guidelines) may have limited generalizability for "marginalized" groups. We proposed the five-step Real-World Data for Genome-Guided Prescribing (ReGGRx) framework and, using All of Us research program (AoU) data, examined its ability to estimate disparities in concordance with and benefit from PGx guidelines for CYP2C19 testing when choosing antiplatelet and antidepressant drugs. The selected measures were intended to identify disparities in avoiding drug failure independent of following PGx guidelines, the odds of avoiding drug failure with PGx concordant treatment, and the degree to which "marginalized" groups (i.e., groups underrepresented in biomedical research [UBR] and with indeterminate CYP2C19 phenotypes) benefit from PGx concordant treatment, when compared with "non-marginalized" groups (i.e., non-UBR and known CYP2C19 phenotypes). Our findings identified disparities in the antidepressant cohort with UBRs (32% of cohort) having a lower odds of avoiding drug failure. For both cohorts, a lower probability of avoiding drug failure was observed in the indeterminate phenotype group (1% of cohorts) than in the known phenotype group, indicating a need to better characterize rare or ancestry-specific risk alleles. With PGx concordant treatment, negative equal opportunity difference values suggested that the UBR group was less likely to avoid drug failure than the non-UBR group. Overall, our findings illustrate the promise of the ReGGRx framework to assess PGx guideline generalizability and produce evidence for use in drug policy decisions.

Indexed as

Antidepressive AgentsGuideline AdherenceHealthcare DisparitiesPharmacogeneticsPharmacogenomic TestingPlatelet Aggregation InhibitorsPrecision MedicineCytochrome P-450 CYP2C19FemaleHumansMalePharmacogenomic VariantsPhenotypePractice Guidelines as TopicAntidepressive AgentsCYP2C19 protein, humanCytochrome P-450 CYP2C19Platelet Aggregation Inhibitorsclinical practice guidelinedisparitiesdrug therapyelectronic health recordsgenotypepharmacogenetic

Identifiers

PMID41707036
PMCPMC12916016

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Registered trials

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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.