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: protocol for a systematic review and individual participant data meta-analysis

Andrea Benedetti; Yin Wu; Brooke Levis; Machelle Wilchesky; Jill Boruff; John P A Ioannidis; Scott B Patten; Pim Cuijpers; Ian Shrier; Simon Gilbody; Zahinoor Ismail; Dean McMillan; Nicholas Mitchell; Roy C Ziegelstein; Brett D Thombs

doi:10.1136/bmjopen-2018-026598

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: protocol for a systematic review and individual participant data meta-analysis

BMJ Open. 2018 Dec 4;8(12):e026598. doi: 10.1136/bmjopen-2018-026598.

Authors

Andrea Benedetti^{1

2

3}, Yin Wu^{1

4

5}, Brooke Levis^{1

4}, Machelle Wilchesky^{4

6}, Jill Boruff⁷, John P A Ioannidis^{8

9}, Scott B Patten^{10

11}, Pim Cuijpers¹², Ian Shrier^{1

4}, Simon Gilbody¹³, Zahinoor Ismail^{10

11

14}, Dean McMillan¹³, Nicholas Mitchell¹⁵, Roy C Ziegelstein¹⁶, Brett D Thombs^{1

3

4

5

17

18}

Affiliations

¹ Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.
² Respiratory Epidemiology and Clinical Research Unit, McGill University Health Centre, Montreal, Quebec, Canada.
³ Department of Medicine, McGill University, Montreal, QC, Canada.
⁴ Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada.
⁵ Department of Psychiatry, McGill University, Montreal, QC, Canada.
⁶ Department of Family Medicine, McGill University, Montreal, Quebec, Canada.
⁷ Schulich Library of Science and Engineering, McGill University, Montreal, Quebec, Canada.
⁸ Stanford Prevention Research Center, Department of Medicine, and Department of Health Research and Policy, Stanford School of Medicine, Stanford, California, USA.
⁹ Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, USA.
¹⁰ Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.
¹¹ Department of Psychiatry, University of Calgary, Calgary, Canada.
¹² Department of Clinical, Neuro and Developmental Psychology and Amsterdam Public Health research institute, VU University Amsterdam, Amsterdam, The Netherlands.
¹³ Hull York Medical School and Department of Health Sciences, The University of York, York, UK.
¹⁴ Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.
¹⁵ Department of Psychiatry, University of Alberta, Edmonton, Canada.
¹⁶ Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, USA.
¹⁷ Department of Psychology, McGill University, Montreal, Canada.
¹⁸ Department of Educational and Counselling Psychology, McGill University, Montreal, Quebec, Canada.

Abstract

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.

Keywords: depression; gds; geriatric depression scale; individual participant data meta-analysis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Aging / psychology*
Depressive Disorder, Major / diagnosis*
Geriatric Assessment / methods*
Humans
Meta-Analysis as Topic
Psychiatric Status Rating Scales
Systematic Reviews as Topic

Grants and funding

CIHR/Canada