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dc.contributor.authorPuac-Polanco, Victor
dc.contributor.authorZiobrowski, Hannah N.
dc.contributor.authorRoss, Eric L.
dc.contributor.authorLiu, Howard
dc.contributor.authorTurner, Brett
dc.contributor.authorCui, Ruifeng
dc.contributor.authorLeung, Lucinda B.
dc.contributor.authorBossarte, Robert M.
dc.contributor.authorBryant, Corey
dc.contributor.authorJoormann, Jutta
dc.contributor.authorNierenberg, Andrew A.
dc.contributor.authorOslin, David W.
dc.contributor.authorPigeon, Wilfred R.
dc.contributor.authorPost, Edward P.
dc.contributor.authorZainal, Nur Hani
dc.contributor.authorZaslavsky, Alan M.
dc.contributor.authorZubizarreta, Jose R.
dc.contributor.authorLuedtke, Alex
dc.contributor.authorKennedy, Chris J.
dc.contributor.authorCipriani, Andrea
dc.contributor.authorFurukawa, Toshiaki A.
dc.contributor.authorKessler, Ronald C.
dc.date.accessioned2023-03-27T16:43:22Z
dc.date.available2023-03-27T16:43:22Z
dc.date.issued2022-07-15
dc.identifier.citationPuac-Polanco, V., Ziobrowski, H. N., Ross, E. L., Liu, H., Turner, B., Cui, R., Leung, L. B., et al. (2022). Development of a model to predict antidepressant treatment response for depression among Veterans. Psychological Medicine, 1–11. Cambridge University Press.en_US
dc.identifier.issn0033-2917
dc.identifier.eissn1469-8978
dc.identifier.doi10.1017/s0033291722001982
dc.identifier.piiS0033291722001982
dc.identifier.urihttp://hdl.handle.net/20.500.12648/8545
dc.description.abstractBackground Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). Methods A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. Results In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (S.E.) of 0.66 (0.04) in the test sample. A strong gradient in probability (S.E.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. Conclusions Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.en_US
dc.language.isoenen_US
dc.publisherCambridge University Press (CUP)en_US
dc.relation.urlhttps://www.cambridge.org/core/journals/psychological-medicine/article/abs/development-of-a-model-to-predict-antidepressant-treatment-response-for-depression-among-veterans/43088350DE0B60F24BCAEF171519F158en_US
dc.rightsCopyright © The Author(s), 2022. Published by Cambridge University Press.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttps://www.cambridge.org/core/terms
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPsychiatry and Mental healthen_US
dc.subjectApplied Psychologyen_US
dc.subjectAntidepressant medicationen_US
dc.subjectClinical Decision supporten_US
dc.subjectDepressionen_US
dc.subjectMachine Learningen_US
dc.subjectTreatment Responseen_US
dc.subjectVeterans Health Administrationen_US
dc.titleDevelopment of a model to predict antidepressant treatment response for depression among Veteransen_US
dc.typeArticle/Reviewen_US
dc.source.journaltitlePsychological Medicineen_US
dc.source.beginpage1
dc.source.endpage11
dc.description.versionAMen_US
refterms.dateFOA2023-03-27T16:43:22Z
dc.description.institutionSUNY Downstateen_US
dc.description.departmentEpidemiology and Biostatisticsen_US
dc.description.departmentHealth Policy and Managementen_US
dc.description.degreelevelN/Aen_US


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