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The identification of biomarkers predicting acute and maintenance lithium treatment response in bipolar disorder: A plea for further research attention

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dc.contributor.authorFornaro, Michele-
dc.contributor.authorDe Berardis, Domenico-
dc.contributor.authorAnastasia, Annalisa-
dc.contributor.authorNovello, Stefano-
dc.contributor.authorFusco, Andrea-
dc.contributor.authorCattaneo, Carlo Ignazio-
dc.contributor.authorSolmi, Marco-
dc.contributor.authorMonaco, Francesco-
dc.contributor.authorVeronese, Nicola-
dc.contributor.authorKim, Yong-Ku-
dc.contributor.authorde Bartolomeis, Andrea-
dc.date.accessioned2021-09-02T04:17:14Z-
dc.date.available2021-09-02T04:17:14Z-
dc.date.created2021-06-19-
dc.date.issued2018-11-
dc.identifier.issn0165-1781-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/72006-
dc.description.abstractThe prediction of acute and maintenance lithium treatment response carries major clinical and neurobiological implications, warranting systematic review. A Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) compliant review searched major electronic databases from inception until December 2017 for studies documenting a clinical diagnosis of bipolar disorder (BD) made according to the mainstream diagnostic manuals and confirmed by a structured interview. Eligible studies allowed a quantitative comparison of endpoint vs baseline mean values of a given biomarker, regardless of the mood phase of patients with BD, and the disorder was assessed for severity using validated rating tool(s). Owing to the purposely applied stringent selection criteria, 16 acute and 12 maintenance studies could be included. The anticipated publication bias limited the chances of reportable generalizable findings, hindering a side-by-side comparison of different records across varying biomarkers and subsequent meta-analyses. The PRISMA approach was nonetheless preferred; it aimed at enhancing the homogeneity of the included results and minimizing the chances of "apples and oranges" with respect to the present research theme. The present critical review confirms the need for future research to specifically assess either pretreatment and/or posttreatment putative biomarkers of patients with BD and treated with lithium.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER IRELAND LTD-
dc.subjectMODERATE-DOSE-USE-
dc.subjectPROPHYLACTIC LITHIUM-
dc.subjectGENE-EXPRESSION-
dc.subjectPERIPHERAL BIOMARKERS-
dc.subjectSARDINIAN PATIENTS-
dc.subjectMESSENGER-RNA-
dc.subjectRATING-SCALE-
dc.subjectASSOCIATION-
dc.subjectDEPRESSION-
dc.subjectMANIA-
dc.titleThe identification of biomarkers predicting acute and maintenance lithium treatment response in bipolar disorder: A plea for further research attention-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Yong-Ku-
dc.identifier.doi10.1016/j.psychres.2018.08.034-
dc.identifier.scopusid2-s2.0-85053082660-
dc.identifier.wosid000449902700097-
dc.identifier.bibliographicCitationPSYCHIATRY RESEARCH, v.269, pp.658 - 672-
dc.relation.isPartOfPSYCHIATRY RESEARCH-
dc.citation.titlePSYCHIATRY RESEARCH-
dc.citation.volume269-
dc.citation.startPage658-
dc.citation.endPage672-
dc.type.rimsART-
dc.type.docTypeReview-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaPsychiatry-
dc.relation.journalWebOfScienceCategoryPsychiatry-
dc.subject.keywordPlusMODERATE-DOSE-USE-
dc.subject.keywordPlusPROPHYLACTIC LITHIUM-
dc.subject.keywordPlusGENE-EXPRESSION-
dc.subject.keywordPlusPERIPHERAL BIOMARKERS-
dc.subject.keywordPlusSARDINIAN PATIENTS-
dc.subject.keywordPlusMESSENGER-RNA-
dc.subject.keywordPlusRATING-SCALE-
dc.subject.keywordPlusASSOCIATION-
dc.subject.keywordPlusDEPRESSION-
dc.subject.keywordPlusMANIA-
dc.subject.keywordAuthorLithium-
dc.subject.keywordAuthorBipolar disorder (BD)-
dc.subject.keywordAuthorBiomarker-
dc.subject.keywordAuthorAcute-
dc.subject.keywordAuthorMaintenance-
dc.subject.keywordAuthorResponse-
dc.subject.keywordAuthorPredictor-
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