TY - JOUR
T1 - Diagnostic accuracy of the Geriatric Depression Scale-30, Geriatric Depression Scale-15, Geriatric Depression Scale-5 and Geriatric Depression Scale-4 for detecting major depression
T2 - Protocol for a systematic review and individual participant data meta-analysis
AU - Benedetti, Andrea
AU - Wu, Yin
AU - Levis, Brooke
AU - Wilchesky, Machelle
AU - Boruff, Jill
AU - Ioannidis, John P.A.
AU - Patten, Scott B.
AU - Cuijpers, Pim
AU - Shrier, Ian
AU - Gilbody, Simon
AU - Ismail, Zahinoor
AU - McMillan, Dean
AU - Mitchell, Nicholas
AU - Ziegelstein, Roy C.
AU - Thombs, Brett D.
N1 - Funding Information:
Funding This research is supported by a grant from the Canadian Institutes of Health Research (CIHR; Funding Reference Number PJT-156365; PIs = Benedetti, Thombs, Wilchesky). Drs Benedetti and Thombs are supported by the Fonds de recherche du Québec - Santé (FRQS) researcher salary award. Dr Wu is supported by an Utting Postdoctoral Fellowship from the Jewish General Hospital, Montreal, Quebec. Ms Levis is supported by a CIHR Frederick Banting and Charles Best Canada Graduate Scholarship doctoral award. Dr Patten is a Senior Health Scholar with Alberta Innovates, Health Solutions. Dr Ismail receives funding from the Alzheimer Society Calgary via the Hotchkiss Brain Institute. Dr Wilchesky is supported by the Donald Berman Maimonides Medical Research Foundation. No funding body had any input into any aspect of this protocol.
Publisher Copyright:
© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Introduction The 30-item Geriatric Depression Scale (GDS-30) and the shorter GDS-15, GDS-5 and GDS-4 are recommended as depression screening tools for elderly individuals. Existing meta-analyses on the diagnostic accuracy of the GDS have not been able to conduct subgroup analyses, have included patients already identified as depressed who would not be screened in practice and have not accounted for possible bias due to selective reporting of results from only better-performing cut-offs in primary studies. Individual participant data meta-analysis (IPDMA), which involves a standard systematic review, then a synthesis of individual participant data, rather than summary results, could address these limitations. The objective of our IPDMA is to generate accuracy estimates to detect major depression for all possible cut-offs of each version of the GDS among studies using different reference standards, separately and among participant subgroups based on age, sex, dementia diagnosis and care settings. In addition, we will use a modelling approach to generate individual participant probabilities for major depression based on GDS scores (rather than a dichotomous cut-off) and participant characteristics (eg, sex, age, dementia status, care setting). Methods and analysis Individual participant data comparing GDS scores to a major depression diagnosis based on a validated structured or semistructured diagnostic interview will be sought via a systematic review. Data sources will include Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO and Web of Science. Bivariate random-effects models will be used to estimate diagnostic accuracy parameters for each cut-off of the different versions of the GDS. Prespecified subgroup analyses will be conducted. Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Ethics and dissemination The findings of this study will be of interest to stakeholders involved in research, clinical practice and policy. PROSPERO registration number CRD42018104329.
AB - Introduction The 30-item Geriatric Depression Scale (GDS-30) and the shorter GDS-15, GDS-5 and GDS-4 are recommended as depression screening tools for elderly individuals. Existing meta-analyses on the diagnostic accuracy of the GDS have not been able to conduct subgroup analyses, have included patients already identified as depressed who would not be screened in practice and have not accounted for possible bias due to selective reporting of results from only better-performing cut-offs in primary studies. Individual participant data meta-analysis (IPDMA), which involves a standard systematic review, then a synthesis of individual participant data, rather than summary results, could address these limitations. The objective of our IPDMA is to generate accuracy estimates to detect major depression for all possible cut-offs of each version of the GDS among studies using different reference standards, separately and among participant subgroups based on age, sex, dementia diagnosis and care settings. In addition, we will use a modelling approach to generate individual participant probabilities for major depression based on GDS scores (rather than a dichotomous cut-off) and participant characteristics (eg, sex, age, dementia status, care setting). Methods and analysis Individual participant data comparing GDS scores to a major depression diagnosis based on a validated structured or semistructured diagnostic interview will be sought via a systematic review. Data sources will include Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO and Web of Science. Bivariate random-effects models will be used to estimate diagnostic accuracy parameters for each cut-off of the different versions of the GDS. Prespecified subgroup analyses will be conducted. Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Ethics and dissemination The findings of this study will be of interest to stakeholders involved in research, clinical practice and policy. PROSPERO registration number CRD42018104329.
KW - depression
KW - gds
KW - geriatric depression scale
KW - individual participant data meta-analysis
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U2 - 10.1136/bmjopen-2018-026598
DO - 10.1136/bmjopen-2018-026598
M3 - Article
C2 - 30518594
AN - SCOPUS:85058222691
SN - 2044-6055
VL - 8
JO - BMJ open
JF - BMJ open
IS - 12
M1 - e026598
ER -