An Analysis of Pharmacogenomic-Guided Pathways and Their Effect on Medication Changes and Hospital Admissions: A Systematic Review and Meta-Analysis.

adverse drug reaction hospital admission medication change medicines optimization patient care pathway pharmacogenetic testing

Journal

Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621

Informations de publication

Date de publication:
2021
Historique:
received: 20 04 2021
accepted: 28 06 2021
entrez: 16 8 2021
pubmed: 17 8 2021
medline: 17 8 2021
Statut: epublish

Résumé

Ninety-five percent of the population are estimated to carry at least one genetic variant that is discordant with at least one medication. Pharmacogenomic (PGx) testing has the potential to identify patients with genetic variants that puts them at risk of adverse drug reactions and sub-optimal therapy. Predicting a patient's response to medications could support the safe management of medications and reduce hospitalization. These benefits can only be realized if prescribing clinicians make the medication changes prompted by PGx test results. This review examines the current evidence on the impact PGx testing has on hospital admissions and whether it prompts medication changes. A systematic search was performed in three databases (Medline, CINAHL and EMBASE) to search all the relevant studies published up to the year 2020, comparing hospitalization rates and medication changes amongst PGx tested patients with patients receiving treatment-as-usual (TAU). Data extracted from full texts were narratively synthesized using a process model developed from the included studies, to derive themes associated to a suggested workflow for PGx-guided care and its expected benefit for medications optimization and hospitalization. A meta-analysis was undertaken on all the studies that report the number of PGx tested patients that had medication change(s) and the number of PGx tested patients that were hospitalized, compared to participants that received TAU. The search strategy identified 5 hospitalization themed studies and 5 medication change themed studies for analysis. The meta-analysis showed that medication changes occurred significantly more frequently in the PGx tested arm across 4 of 5 studies. Meta-analysis showed that all-cause hospitalization occurred significantly less frequently in the PGx tested arm than the TAU. The results show proof of concept for the use of PGx in prescribing that produces patient benefit. However, the review also highlights the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems; namely patient involvement in PGx prescribing decisions, thus a better understanding of the perspective of patients and prescribers. We highlight the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems.

Identifiants

pubmed: 34394187
doi: 10.3389/fgene.2021.698148
pmc: PMC8362615
doi:

Types de publication

Systematic Review

Langues

eng

Pagination

698148

Informations de copyright

Copyright © 2021 David, Fylan, Bryant, Smith, Sagoo and Rattray.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Victoria David (V)

Leeds Teaching Hospitals National Health Service (NHS) Trust, Leeds, United Kingdom.
School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.
Wolfson Centre for Applied Health Research, Bradford, United Kingdom.

Beth Fylan (B)

School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.
Wolfson Centre for Applied Health Research, Bradford, United Kingdom.
Yorkshire and Humber Patient Safety Translational Research Centre, Bradford Institute of Health Research, Bradford, United Kingdom.

Eleanor Bryant (E)

Wolfson Centre for Applied Health Research, Bradford, United Kingdom.
Division of Psychology in the School of Social Sciences, University of Bradford, Bradford, United Kingdom.

Heather Smith (H)

Leeds Teaching Hospitals National Health Service (NHS) Trust, Leeds, United Kingdom.

Gurdeep S Sagoo (GS)

Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.
National Institute for Health Research Leeds In Vitro Diagnostics Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom.

Marcus Rattray (M)

School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.
Wolfson Centre for Applied Health Research, Bradford, United Kingdom.

Classifications MeSH