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Predicting therapeutic response to oral ketamine for chronic suicidal ideation- a Bayesian network for clinical decision support2.36 MB
Published VersionCC BY V4.0, Open Access
Journal article
Predicting therapeutic response to oral ketamine for chronic suicidal ideation: a Bayesian network for clinical decision support
BMC Psychiatry, Vol.20(1), pp.1-15
2020
PMID: 33115424
Appears in Thompson Institute Research Collection
Abstract
Background: The glutamatergic modulator ketamine has been shown to result in rapid reductions in both suicidal ideation (SI) and depressive symptoms in clinical trials. There is a practical need for identification of pre-treatment predictors of ketamine response. Previous studies indicate links between treatment response and body mass index (BMI), depression symptoms and previous suicide attempts. Our aim was to explore the use of clinical and demographic factors to predict response to serial doses of oral ketamine for chronic suicidal ideation. Methods: Thirty-two participants completed the Oral Ketamine Trial on Suicidality (OKTOS). Data for the current study were drawn from pre-treatment and follow-up time-points of OKTOS. Only clinical and sociodemographic variables were included in this analysis. Data were used to create a proof of concept Bayesian network (BN) model of variables predicting prolonged response to oral ketamine, as defined by the Beck Scale for Suicide Ideation (BSS). Results: The network of potential predictors of response was evaluated using receiver operating characteristic (ROC) curve analyses. A combination of nine demographic and clinical variables predicted prolonged ketamine response, with strong contributions from BMI, Social and Occupational Functioning Assessment Scale (SOFAS), Montgomery-Asberg Depression Rating Scale (MADRS), number of suicide attempts, employment status and age. We evaluated and optimised the proposed network to increase the area under the ROC curve (AUC). The performance evaluation demonstrated that the BN predicted prolonged ketamine response with 97% accuracy, and AUC = 0.87. Conclusions: At present, validated tools to facilitate risk assessment are infrequently used in psychiatric practice. Pre-treatment assessment of individuals’ likelihood of response to oral ketamine for chronic suicidal ideation could be beneficial in making more informed decisions about likelihood of success for this treatment course. Clinical trials registration number ACTRN12618001412224, retrospectively registered 23/8/2018.
Details
- Title
- Predicting therapeutic response to oral ketamine for chronic suicidal ideation: a Bayesian network for clinical decision support
- Authors
- Denise Beaudequin (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteAdem Can (Author) - University of the Sunshine Coast, Queensland, School of Social Sciences - LegacyMegan Dutton (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteMonique Jones (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteCyrana Gallay (Author) - University of the Sunshine Coast, Queensland, Thompson InstitutePaul Schwenn (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteCian Yang (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteGrace Forsyth (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteGabrielle Simcock (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteDaniel Hermens (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteJim Lagopoulos (Author) - University of the Sunshine Coast, Queensland, Thompson Institute
- Publication details
- BMC Psychiatry, Vol.20(1), pp.1-15
- Publisher
- BioMed Central Ltd.
- Date published
- 2020
- DOI
- 10.1186/s12888-020-02925-1
- ISSN
- 1471-244X
- PMID
- 33115424
- Copyright note
- © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
- Organisation Unit
- School of Social Sciences - Legacy; University of the Sunshine Coast, Queensland; Office of Research; Thompson Institute
- Language
- English
- Record Identifier
- 99485608802621
- Output Type
- Journal article
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