First Report of Pharmacogenomic Profiling in an Outpatient Spine Setting: Preliminary Results from a Pilot Study.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
01 2021
Historique:
received: 13 07 2020
revised: 01 09 2020
accepted: 02 09 2020
pubmed: 12 9 2020
medline: 22 6 2021
entrez: 11 9 2020
Statut: ppublish

Résumé

Pharmacogenomics may help personalize medicine and improve therapeutic selection. This is the first study investigating how pharmacogenomic testing may inform analgesic selection in patients with spine disease. We profile pharmacogenetic differences in pain medication-metabolizing enzymes across patients presenting at an outpatient spine clinic and provide preliminary evidence that genetic polymorphisms may help explain interpatient differences in preoperative pain refractory to conservative management. Adults presenting to our outpatient spine clinic with chief symptoms of neck and/or back pain were prospectively enrolled over 9 months. Patients completed the Wong-Baker FACES and numeric pain rating scales for their chief pain symptom and provided detailed medication histories and cheek swab samples for genomic analysis. Thirty adults were included (mean age, 60.6 ± 15.3 years). The chief concern was neck pain in 23%, back pain in 67%, and combined neck/back pain in 10%. At enrollment, patient analgesic regimens comprised 3 ± 1 unique medications, including 1 ± 1 opioids. After genomic analysis, 14/30 patients (47%) were identified as suboptimal metabolizers of ≥1 medications in their analgesic regimen. Of these patients, 93% were suboptimal metabolizers of their prescribed opioid analgesic. Nonetheless, pain scores were similar between optimal and suboptimal metabolizer groups. This pilot study shows that a large proportion of the spine outpatient population may use pain medications for which they are suboptimal metabolizers. Further studies should assess whether these pharmacogenomic differences indicate differences in odds of receiving therapeutic benefit from surgery or if they can be used to generate more effective postoperative analgesic regimens.

Identifiants

pubmed: 32916348
pii: S1878-8750(20)32015-5
doi: 10.1016/j.wneu.2020.09.007
pii:
doi:

Substances chimiques

Analgesics 0
Analgesics, Opioid 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e21-e31

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Ethan Cottrill (E)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Zach Pennington (Z)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

A Karim Ahmed (AK)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Bowen Jiang (B)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Jeff Ehresman (J)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Alex Zhu (A)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Alexander Perdomo-Pantoja (A)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Daniel Lubelski (D)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Daniel M Sciubba (DM)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Timothy Witham (T)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Kevin MacDonald (K)

Advanced Genomic Solutions (AGS) Ltd., Scottsdale, Arizona, USA.

Chun Hin Lee (CH)

Advanced Genomic Solutions (AGS) Ltd., Scottsdale, Arizona, USA.

Chun Wan Jeffrey Lai (CWJ)

Advanced Genomic Solutions (AGS) Ltd., Scottsdale, Arizona, USA.

Nicholas Theodore (N)

Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA. Electronic address: theodore@jhmi.edu.

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Classifications MeSH