Literature DB >> 31593971

The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis.

Chen He1,2, Brooke Levis1,2, Kira E Riehm1, Nazanin Saadat1, Alexander W Levis1,2, Marleine Azar1,2, Danielle B Rice1,3, Ankur Krishnan1, Yin Wu1,2,4, Ying Sun1, Mahrukh Imran1, Jill Boruff5, Pim Cuijpers6, Simon Gilbody7, John P A Ioannidis8, Lorie A Kloda9, Dean McMillan7, Scott B Patten10,11, Ian Shrier1,2, Roy C Ziegelstein12, Dickens H Akena13, Bruce Arroll14, Liat Ayalon15, Hamid R Baradaran16,17, Murray Baron1,18, Anna Beraldi19, Charles H Bombardier20, Peter Butterworth21,22, Gregory Carter23, Marcos Hortes Nisihara Chagas24, Juliana C N Chan24,25,26, Rushina Cholera27, Kerrie Clover23,28, Yeates Conwell29, Janneke M de Man-van Ginkel30, Jesse R Fann31, Felix H Fischer32, Daniel Fung33,34,35,36, Bizu Gelaye37, Felicity Goodyear-Smith14, Catherine G Greeno38, Brian J Hall39,40, Patricia A Harrison41, Martin Härter42, Ulrich Hegerl43, Leanne Hides44, Stevan E Hobfoll45, Marie Hudson1,18, Thomas N Hyphantis46, Masatoshi Inagaki47, Khalida Ismail48, Nathalie Jetté10,11,49, Mohammad E Khamseh16, Kim M Kiely50,51, Yunxin Kwan52, Femke Lamers53, Shen-Ing Liu36,54,55,56, Manote Lotrakul57, Sonia R Loureiro49, Bernd Löwe58, Laura Marsh59, Anthony McGuire60, Sherina Mohd-Sidik61, Tiago N Munhoz62, Kumiko Muramatsu63, Flávia L Osório49,64, Vikram Patel65,66, Brian W Pence67, Philippe Persoons68,69, Angelo Picardi70, Katrin Reuter71, Alasdair G Rooney72, Iná S da Silva Dos Santos62, Juwita Shaaban73, Abbey Sidebottom74, Adam Simning29, Lesley Stafford75,76, Sharon Sung33,36, Pei Lin Lynnette Tan52, Alyna Turner77,78, Henk C P M van Weert79, Jennifer White80, Mary A Whooley81,82,83, Kirsty Winkley84, Mitsuhiko Yamada85, Brett D Thombs86,87,88,89,90,91, Andrea Benedetti2,18,92.   

Abstract

BACKGROUND: Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results.
OBJECTIVE: To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10.
METHODS: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview.
RESULTS: Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88).
CONCLUSIONS: The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.
© 2019 S. Karger AG, Basel.

Entities:  

Keywords:  Depression; Diagnostic accuracy; Meta-analysis; Patient Health Questionnaire-9; Screening

Mesh:

Year:  2019        PMID: 31593971      PMCID: PMC6960351          DOI: 10.1159/000502294

Source DB:  PubMed          Journal:  Psychother Psychosom        ISSN: 0033-3190            Impact factor:   25.617


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