The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis
Creators: name: Hudson, M
name: Baradaran, H.R
name: Gelaye, B
name: Cuijpers, P
name: Patel, V
name: Tan, P.L.L.
name: McMillan, D
name: Lamers, F
name: Hides, L
name: Lotrakul, M
name: Saadat, N.
name: Shaaban, J
name: De Man-Van Ginkel, J.M
name: Beraldi, A
name: Chagas, M.H.N
name: Härter, M
name: Ioannidis, J.P.A
name: Inagaki, M
name: Turner, A.
name: He, C.
name: Conwell, Y
name: Shrier, I
name: Ayalon, L
name: Sung, S
name: Fischer, F.H
name: Hegerl, U
name: Cholera, R
name: Levis, B.
name: Gilbody, S
name: Kiely, K.M
name: Akena, D.H
name: Reuter, K
name: Goodyear-Smith, F
name: Chan, J.C.N
name: Simning, A
name: Yamada, M.
name: Ziegelstein, R.C
name: Boruff, J
name: Sun, Y
name: Persoons, P
name: Löwe, B
name: Jetté, N
name: White, J.
name: Greeno, C.G
name: Winkley, K.
name: Da Silva Dos Santos, I.S
name: Baron, M
name: Rice, D.B.
name: Munhoz, T.N
name: Osório, F.L
name: Benedetti, A.
name: Clover, K
name: Hobfoll, S.E
name: Khamseh, M.E
name: Harrison, P.A
name: Kwan, Y
name: Sidebottom, A
name: Riehm, K.E.
name: McGuire, A
name: Hall, B.J
name: Arroll, B
name: Ismail, K
name: Wu, Y.
name: Loureiro, S.R
name: Hyphantis, T.N
name: Marsh, L
name: Azar, M.
name: Van Weert, H.C.P.M.
name: Imran, M
name: Whooley, M.A.
name: Picardi, A
name: Liu, S.-I
name: Muramatsu, K
name: Levis, A.W.
name: Thombs, B.D.
name: Fung, D
name: Bombardier, C.H
name: Fann, J.R
name: Carter, G
name: Kloda, L.A
name: Krishnan, A.
name: Patten, S.B
name: Rooney, A.G.
name: Pence, B.W
name: Butterworth, P
name: Mohd-Sidik, S
name: Stafford, L
Publisher: name: S. Karger AG
Year: 2020

description: 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.