This study is a protocol for a systematic review and individual patient data meta-analysis to determine the diagnostic accuracy of the HADS-D for detecting major depression; no results are reported.
Meta-Analysis
Does the HADS-D accurately detect major depression in adults compared to a structured clinical interview?
This protocol outlines an individual patient data meta-analysis to determine the diagnostic accuracy of the HADS-D for major depression and to develop a predictive algorithm.
INTRODUCTION: The Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) has been recommended for depression screening in medically ill patients. Many existing HADS-D studies have used exploratory methods to select optimal cut-offs. Often, these studies report results from a small range of cut-off thresholds; cut-offs with more favourable accuracy results are more likely to be reported than others with worse accuracy estimates. When published data are combined in meta-analyses, selective reporting may generate biased summary estimates. Individual patient data (IPD) meta-analyses can address this problem by estimating accuracy with data from all studies for all relevant cut-off scores. In addition, a predictive algorithm can be generated to estimate the probability that a patient has depression based on a HADS-D score and clinical characteristics rather than dichotomous screening classification alone. The primary objectives of our IPD meta-analyses are to determine the diagnostic accuracy of the HADS-D to detect major depression among adults across all potentially relevant cut-off scores and to generate a predictive algorithm for individual patients. We are already aware of over 100 eligible studies, and more may be identified with our comprehensive search. METHODS AND ANALYSIS: Data sources will include MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO and Web of Science. Eligible studies will have datasets where patients are assessed for major depression based on a validated structured or semistructured clinical interview and complete the HADS-D within 2 weeks (before or after). Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Bivariate random-effects meta-analysis will be conducted for the full range of plausible cut-off values, and a predictive algorithm for individual patients will be generated. ETHICS AND DISSEMINATION: The findings of this study will be of interest to stakeholders involved in research, clinical practice and policy.
Thombs et al. (Fri,) conducted a meta-analysis in Major depression. Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) vs. Validated structured or semistructured clinical interview was evaluated on Diagnostic accuracy of the HADS-D to detect major depression across all potentially relevant cut-off scores. This study is a protocol for a systematic review and individual patient data meta-analysis to determine the diagnostic accuracy of the HADS-D for detecting major depression; no results are reported.