Prediction of opioid dose in cancer pain patients using genetic profiling: not yet an option with support vector machine learning

Autor:	Mikkel Gram, Asbjørn Mohr Drewes, Frank Skorpen, Pål Klepstad, Anne Estrup Olesen, Debbie Grønlund
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	Male Support vector machine Genotype medicine.drug_class Analgesic Receptors Opioid mu lcsh:Medicine Single-nucleotide polymorphism Bioinformatics Catechol O-Methyltransferase Polymorphism Single Nucleotide General Biochemistry Genetics and Molecular Biology 03 medical and health sciences 0302 clinical medicine Gene Frequency 030202 anesthesiology Opioid receptor Receptors Opioid delta Journal Article Genetics Medicine Humans Genetic variability Cancer pain lcsh:Science (General) lcsh:QH301-705.5 Aged Dose-Response Relationship Drug Morphine business.industry lcsh:R General Medicine Pain management Middle Aged Analgesics Opioid Research Note Opioid lcsh:Biology (General) Female business 030217 neurology & neurosurgery medicine.drug SNPs lcsh:Q1-390
Zdroj:	BMC Research Notes, Vol 11, Iss 1, Pp 1-5 (2018) Olesen, A E, Grønlund, D, Gram, M, Skorpen, F, Drewes, A M & Klepstad, P 2018, ' Prediction of opioid dose in cancer pain patients using genetic profiling : Not yet an option with support vector machine learning ', BMC Research Notes, vol. 11, 78 . https://doi.org/10.1186/s13104-018-3194-z Olesen, A E, Grønlund, D, Gram, M, Skorpen, F, Drewes, A M & Klepstad, P 2018, ' Prediction of opioid dose in cancer pain patients using genetic profiling : not yet an option with support vector machine learning ', BMC Research Notes, vol. 11, no. 1, 78 . https://doi.org/10.1186/s13104-018-3194-z 78-? BMC Research Notes
ISSN:	1756-0500
DOI:	10.1186/s13104-018-3194-z
Popis:	Objective Use of opioids for pain management has increased over the past decade; however, inadequate analgesic response is common. Genetic variability may be related to opioid efficacy, but due to the many possible combinations and variables, statistical computations may be difficult. This study investigated whether data processing with support vector machine learning could predict required opioid dose in cancer pain patients, using genetic profiling. Eighteen single nucleotide polymorphisms (SNPs) within the µ and δ opioid receptor genes and the catechol-O-methyltransferase gene were selected for analysis. Results Data from 1237 cancer pain patients were included in the analysis. Support vector machine learning did not find any associations between the assessed SNPs and opioid dose in cancer pain patients, and hence, did not provide additional information regarding prediction of required opioid dose using genetic profiling. © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5e61da2125711c4dd07f55e18dd3831 http://link.springer.com/article/10.1186/s13104-018-3194-z Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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