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Targeting treatments for depression: what can our patients tell us?

Published online by Cambridge University Press:  05 April 2016

A. John Rush
A. John Rush*
Affiliation:
Duke-National University of Singapore, Singapore
*
Address for correspondence: A. J. Rush, Duke-National University of Singapore, 6, The Academia, 20 College Road, 169856, Singapore. (Email: john.rush@duke-nus.edu.sg)
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Abstract

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Keywords

Depressiontreatment selectionclinical indicators

Information

Type
Commentary to Special Article
Information
Epidemiology and Psychiatric Sciences , Volume 26 , Issue 1 , February 2017 , pp. 37 - 39
Copyright
Copyright © Cambridge University Press 2016 

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References

Etkin, A, Patenaude, B, Song, YJC, Usherwood, T, Rekshan, W, Schatzberg, AF, Rush, AJ, Williams, LM (2015). A cognitive-emotional biomarker for predicting remission with antidepressant medications: a report from the iSPOT-D trial. Neuropsychopharmacology 40, 1332–1342.CrossRefGoogle ScholarPubMed
Judd, LL, Schettler, PJ, Rush, AJ, Coryell, WH, Fiedorowicz, JG, Solomon, DA (2015). A new empirical definition of major depressive episode recovery and its positive impact on future course of illness. Journal of Clinical Psychiatry (epub ahead of print). doi: 10.4088/JCP.15m09918.Google Scholar
Korgaonkar, MS, Rekshan, W, Gordon, E, Rush, AJ, Williams, LM, Blasey, C, Grieve, SM (2014). Magnetic resonance imaging measures of brain structure to predict antidepressant treatment outcome in major depressive disorder. EBioMedicine 2, 37–45. doi: 10.1016/j.ebiom.2014.12.002.CrossRefGoogle ScholarPubMed
Kuk, A, Li, J, Rush, AJ (2010). Recursive subsetting: a method to enhance the accuracy of early prediction of treatment outcome and to inform personalized care. Journal of Clinical Psychiatry 71, 1502–1508.CrossRefGoogle ScholarPubMed
Lavori, PW, Rush, AJ, Wisniewski, S, Alpert, J, Fava, M, Kupfer, DJ, Nierenberg, A, Quitkin, FM, Sackeim, HA, Thase, ME, Trivedi, M (2001). Strengthening clinical effectiveness trials: equipoise-stratified randomization. Biological Psychiatry 50, 792–801.CrossRefGoogle ScholarPubMed
Li, J, Kuk, A, Rush, AJ (2012). A practical approach to the early identification of antidepressant medication non-responders. Psychological Medicine 42, 309–316.CrossRefGoogle Scholar
Rush, AJ (2007). STAR*D: what have we learned? [special article]. American Journal of Psychiatry 164, 201–204.CrossRefGoogle ScholarPubMed
Rush, AJ (2015). Isn't it about time to employ measurement-based Care in practice? American Journal of Psychiatry 172, 934–936.CrossRefGoogle ScholarPubMed
Rush, AJ, Fava, M, Wisniewski, SR, Lavori, PW, Trivedi, MH, Sackeim, HA, Thase, ME, Nierenberg, AA, Quitkin, FM, Kashner, TM, Kupfer, DJ, Rosenbaum, JF, Alpert, J, Stewart, J, McGrath, PJ, Biggs, MM, Shores-Wilson, K, Lebowitz, BD, Ritz, L, Niederehe, G, for the STAR*D Investigators Group (2004). Sequenced Treatment Alternatives to Relieve Depression (STAR*D): rationale and design. Controlled Clinical Trials 25, 119–142.CrossRefGoogle ScholarPubMed
Rush, AJ, Trivedi, MH, Wisniewski, SR, Nierenberg, AA, Stewart, JW, Warden, D, Niederehe, G, Thase, ME, Lavori, PW, Lebowitz, BD, McGrath, PJ, Rosenbaum, JF, Sackeim, HA, Kupfer, DJ, Luther, J, Fava, M (2006). Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. American Journal of Psychiatry 163, 1905–1917.CrossRefGoogle ScholarPubMed
Rush, AJ, Wisniewski, SR, Warden, D, Luther, JF, Davis, LL, Fava, M, Nierenberg, AA, Trivedi, MH (2008). Selecting among second-step antidepressant medication monotherapies. Predictive value of clinical, demographic, or first-step treatment features. Archives of General Psychiatry 65, 870–881.CrossRefGoogle ScholarPubMed
Rush, AJ, Warden, D, Wisniewski, SR, Fava, M, Trivedi, MH, Gaynes, BN, Nierenberg, AA (2009). STAR*D: revising conventional wisdom. CNS Drugs 23, 627–647.Google ScholarPubMed
Schatzberg, AF, DeBattista, C, Lazzeroni, LC, Etkin, A, Murphy, GM Jr., Williams, LM (2015). ABCB1 Genetic effects on antidepressant outcomes: a report from the i-SPOT-D. American Journal of Psychiatry 172, 751–759.CrossRefGoogle Scholar
Wisniewski, SR, Rush, AJ, Nierenberg, AA, Gaynes, BN, Warden, D, Luther, JF, McGrath, PJ, Lavori, PW, Thase, ME, Fava, M, Trivedi, MH (2009). Can Phase III trial results of antidepressant medications be generalized to clinical practice? A STAR*D report. American Journal of Psychiatry 166, 599–607.CrossRefGoogle ScholarPubMed