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Objectives: Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale - depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence., Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated., Results: 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was -21.1% to 19.5%., Conclusions: HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D)., Methods: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores., Results: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96))., Conclusion: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: Database searches for studies of diagnostic test accuracy are notoriously difficult to filter, highly resource-intensive, and a potential barrier to quality evidence synthesis. We examined published meta-analyses of depression screening tool accuracy to evaluate the (1) proportion of included primary studies found in any online database in the original meta-analyses that were indexed in MEDLINE; (2) the proportion of patients from MEDLINE-indexed studies; and (3) the proportion of depression cases from studies indexed in MEDLINE., Methods: MEDLINE and PsycINFO were searched from January 1, 2005 through October 31, 2014 for meta-analyses in any language on the accuracy of depression screening tools., Results: We identified 16 eligible meta-analyses that included 398 primary study citations, which had been identified via an online database in the original meta-analyses, including 257 unique citations and 234 unique patient samples. The 234 unique patient samples included 69,957 total patients and 11,867 depression cases. Of these, 220 samples (94%) were from studies indexed in MEDLINE, including 97% of all patients and 96% of all depression cases. When applying a peer-reviewed search strategy in MEDLINE, 91% of all samples, 96% of patients and 95% of depression cases were retrieved. Results were similar for total and unique citations., Conclusions: Restricting searches to MEDLINE may capture almost all eligible studies, patients and depression cases. Although not examined in the present study, MEDLINE may not be indexed as quickly as other databases. Thus, MEDLINE searches should be complemented by date-limited searches of other databases for recent citations., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objective: Meta-analyses that are conducted rigorously and reported completely and transparently can provide accurate evidence to inform the best possible healthcare decisions. Guideline makers have raised concerns about the utility of existing evidence on the diagnostic accuracy of depression screening tools. The objective of our study was to evaluate the transparency and completeness of reporting in meta-analyses of the diagnostic accuracy of depression screening tools using the PRISMA tool adapted for diagnostic test accuracy meta-analyses., 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 the transparency in reporting using the PRISMA tool with appropriate adaptations made for studies of diagnostic test accuracy., Results: We identified 21 eligible meta-analyses. Twelve of 21 meta-analyses complied with at least 50% of adapted PRISMA items. Of 30 adapted PRISMA items, 11 were fulfilled by ≥80% of included meta-analyses, 3 by 50-79% of meta-analyses, 7 by 25-45% of meta-analyses, and 9 by <25%. On average, post-PRISMA meta-analyses complied with 17 of 30 items compared to 13 of 30 items pre-PRISMA., Conclusions: Deficiencies in the transparency of reporting in meta-analyses of the diagnostic test accuracy of depression screening tools of meta-analyses were identified. Authors, reviewers, and editors should adhere to the PRISMA statement to improve the reporting of meta-analyses of the diagnostic accuracy of depression screening tools., (Copyright © 2016 Elsevier Inc. All rights reserved.)

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., (Copyright © 2016 Elsevier Inc. All rights reserved.)