Please use this identifier to cite or link to this item: https://doi.org/10.1017/S0033291711001280
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dc.titleA practical approach to the early identification of antidepressant medication non-responders
dc.contributor.authorLi, J.
dc.contributor.authorKuk, A.Y.C.
dc.contributor.authorRush, A.J.
dc.date.accessioned2014-11-26T09:03:28Z
dc.date.available2014-11-26T09:03:28Z
dc.date.issued2012-02
dc.identifier.citationLi, J., Kuk, A.Y.C., Rush, A.J. (2012-02). A practical approach to the early identification of antidepressant medication non-responders. Psychological Medicine 42 (2) : 309-316. ScholarBank@NUS Repository. https://doi.org/10.1017/S0033291711001280
dc.identifier.issn00332917
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/110475
dc.description.abstractBackground The aim of the present study was to determine whether a combination of baseline features and early post-baseline depressive symptom changes have clinical value in predicting out-patient non-response in depressed out-patients after 8 weeks of medication treatment.Method We analysed data from the Combining Medications to Enhance Depression Outcomes study for 447 participants with complete 16-item Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR 16) ratings at baseline and at treatment weeks 2, 4 and 8. We used a multi-time point, recursive subsetting approach that included baseline features and changes in QIDS-SR 16 scores from baseline to weeks 2 and 4, to identify non-responders (
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1017/S0033291711001280
dc.sourceScopus
dc.subjectAntidepressant medication
dc.subjectcross-validation
dc.subjectdiagnostic medicine
dc.subjectnegative predictive value
dc.subjectrecursive subsetting
dc.typeArticle
dc.contributor.departmentDUKE-NUS GRADUATE MEDICAL SCHOOL S'PORE
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1017/S0033291711001280
dc.description.sourcetitlePsychological Medicine
dc.description.volume42
dc.description.issue2
dc.description.page309-316
dc.description.codenPSMDC
dc.identifier.isiut000299887700008
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