Methodological quality of meta-analyses of the diagnostic accuracy of depression screening tools.
OBJECTIVE
Concerns have been raised that primary studies of diagnostic accuracy of depression screening tools may exaggerate estimates of accuracy and that this could also influence the results of meta-analyses. No studies, however, have evaluated the quality of meta-analyses of depression screening tools. Our objective was to evaluate the quality of meta-analyses of the diagnostic accuracy of depression screening tools.


METHODS
We searched MEDLINE and PsycINFO from January 1, 2005 through March 13, 2016 for recent meta-analyses in any language on the diagnostic accuracy of depression screening tools. Two reviewers independently assessed methodological quality using the AMSTAR tool with appropriate adaptations made for studies of diagnostic test accuracy.


RESULTS
We identified 21 eligible meta-analyses. The majority provided a list of included studies (100%), included a comprehensive literature search (95%) and assessed risk of bias of included studies (71%). Meta-analyses less consistently included non-published evidence (38%), listed excluded studies (33%), incorporated risk of bias findings into conclusions (33%), and assessed selective cutoff reporting (29%). Meta-analyses rarely reported that duplicate study selection or data extraction occurred (14%), mentioned 'a priori' protocols (10%), or reported on conflicts of interest (0%) or funding sources (0%) of primary studies. Only 6 of 21 included meta-analyses complied with at least 7 of 14 adapted AMSTAR items.


CONCLUSIONS
The methodological quality of most meta-analyses of the diagnostic test accuracy of depression screening tools is suboptimal. Improving quality will reduce the risk of inaccurate estimates of accuracy and inappropriate inferences.
Department of Psychiatry, McGill University, Montreal, Canada; Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada.
Danielle B
DB
Rice
Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada; Department of Epidemiology, Biostatistics, and Occupational Health, Montreal, Canada.
Ian
I
Shrier
Library, Concordia University, Montreal, Canada.
Lorie A
LA
Kloda
Department of Epidemiology, Biostatistics, and Occupational Health, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, McGill University Health Centre, Montreal, Canada.
Andrea
A
Benedetti
Department of Psychiatry, McGill University, Montreal, Canada; Department of Epidemiology, Biostatistics, and Occupational Health, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Department of Educational and Counselling Psychology, McGill University, Montreal, Canada; Department of Psychology, McGill University, Montreal, Canada. Electronic address: brett.thombs@mcgill.ca.
Brett D
BD
Thombs
D003863:Depression / Q000175:diagnosis*; D003866:Depressive Disorder / Q000175:diagnosis*; D006801:Humans; D008403:Mass Screening / Q000379:methods / Q000592:standards; D015201:Meta-Analysis as Topic
AMSTAR; Depression; Diagnostic test accuracy; Meta-analyses; Quality; Screening