Evidence map›Paper›PMID 39967300›Full record

ArticleClinical and translational science2025

Real-World Utilization of Medications With Pharmacogenetic Recommendations in Older Adults: A Scoping Review.

Bella D Ianni, Chin Hang Yiu, Edwin C K Tan, Christine Y Lu

Abstract readScoping Review
In one paragraph

Article in Clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. A systematic review of real-world evidence on the clinical relevance, characterization, and utility ofJournal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2025
    Pooled it
  2. Article
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

4 authors.

Bella D IanniThe University of Sydney, School of Pharmacy, Sydney, New South Wales, Australia.ORCID 0009-0004-9771-3986
Chin Hang YiuThe University of Sydney, School of Pharmacy, Sydney, New South Wales, Australia.ORCID 0000-0001-7758-6087
Edwin C K TanThe University of Sydney, School of Pharmacy, Sydney, New South Wales, Australia.ORCID 0000-0003-2922-8837
Christine Y LuThe University of Sydney, School of Pharmacy, Sydney, New South Wales, Australia.ORCID 0000-0002-7550-6837

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pharmacogenetic testing provides patient genotype information which could influence medication selection and dosing for optimal patient care. Insurance coverage for pharmacogenetic testing varies widely. A better understanding of the commonly used medications with clinically important pharmacogenetic recommendations can inform which medications and/or genes should be prioritized for coverage and reimbursement in the context of finite healthcare resources. The aim of this scoping review was to collate previous studies that investigated the utilization rate of medications that could be guided by pharmacogenetic testing. Included studies utilized electronic medical records or claims data to assess pharmacogenetic medication prescription rates for older adults (≥ 65 years old). Identified pharmacogenetic medications were classified according to therapeutic class and assessed for actionability based on the Clinical Pharmacogenetics Implementation Consortium guidelines. Across the 31 included studies, analgesic (n = 29), psychotropic (n = 29), and cardiovascular (n = 27) therapeutic classes were most commonly investigated. Study populations were primarily generalized (48%); however, some studies focused on specific populations, such as, cancer (n = 6), mental health (n = 1), and nursing home (n = 2) cohorts. A total of 215 unique pharmacogenetic medications were reported, of which, 82 were associated with actionable pharmacogenetic recommendations. The most frequent genes implicated in potential drug-gene interactions with these actionable pharmacogenetic drugs were CYP2D6 (25.6%), CYP2C19 (18.3%), and CYP2C9 (11%). Medications most frequently prescribed included pantoprazole (range 0%-49.6%), simvastatin (range 0%-54.9%), and ondansetron (range 0.1%-62.6%). Overall, the frequently prescribed medications and associated genes identified in this review could guide pharmacogenetic testing implementation into clinical practice, including insurer subsidization.

Indexed as

PharmacogeneticsPharmacogenomic TestingAgedAged, 80 and overHumansclaims datadrug utilizationelectronic medical recordsolder adultsPGxpharmacogeneticspharmacogenomicsprecision medicineprescription ratesreal‐world data

Identifiers

PMID39967300
PMCPMC11836345

What OpenQuestion holds

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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.