The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis
Authors: He Chen , Levis Brooke , Riehm Kira E. , Saadat Nazanin , Levis Alexander W. , Azar Marleine , Rice Danielle B. , Krishnan Ankur , Wu Yin , Sun Ying , Imran Mahrukh , Boruff Jill , Cuijpers Pim , Gilbody Simon , Ioannidis John P.A. , Kloda Lorie A. , McMillan Dean , Patten Scott B. , Shrier Ian , Ziegelstein Roy C. , Akena Dickens H. , Arroll Bruce , Ayalon Liat , Baradaran Hamid R. , Baron Murray , Beraldi Anna , Bombardier Charles H. , Butterworth Peter , Carter Gregory , Chagas Marcos Hortes Nisihara , Chan Juliana C.N. , Cholera Rushina , Clover Kerrie , Conwell Yeates , de Man-van Ginkel Janneke M. , Fann Jesse R. , Fischer Felix H. , Fung Daniel , Gelaye Bizu  , Goodyear-Smith Felicity , Greeno Catherine G. , Hall Brian J. , Harrison Patricia A. , Härter Martin , Hegerl Ulrich , Hides Leanne , Hobfoll Stevan E. , Hudson Marie , Hyphantis Thomas N. , Inagaki Masatoshi , Ismail Khalida , Jetté Nathalie , Khamseh Mohammad E. , Kiely Kim M. , Kwan Yunxin , Lamers Femke , Liu Shen-Ing , Lotrakul Manote , Loureiro Sonia R. , Löwe Bernd , Marsh Laura , McGuire Anthony , Mohd-Sidik Sherina , Munhoz Tiago N. , Muramatsu Kumiko , Osório Flávia L. , Patel Vikram , Pence Brian W. , Persoons Philippe , Picardi Angelo , Reuter Katrin , Rooney Alasdair G. , da Silva dos Santos Iná S. , Shaaban Juwita , Sidebottom Abbey , Simning Adam , Stafford Lesley , Sung Sharon , Tan Pei Lin Lynnette , Turner Alyna , van Weert Henk C.P.M. , White Jennifer , Whooley Mary A. , Winkley Kirsty , Yamada Mitsuhiko , Thombs Brett D. , Benedetti Andrea 
Published: October 2019

<b><i>Background:</i></b> 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. <b><i>Objective:</i></b> 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. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> Data were included for 54 of 72 identified eligible studies (<i>n</i> participants = 16,688, <i>n</i> 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). <b><i>Conclusions:</i></b> The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.