The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis
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Publication date
2020-01
Authors
He, Chen
Levis, Brooke
Riehm, Kira E
Saadat, Nazanin
Levis, Alexander W
Azar, Marleine
Rice, Danielle B
Krishnan, Ankur
Wu, Yin
Sun, Ying
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Document Type
Article
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taverne
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.
Keywords
Depression, Diagnostic accuracy, Meta-analysis, Patient Health Questionnaire-9, Screening, Taverne, Clinical Psychology, Applied Psychology, Psychiatry and Mental health
Citation
He, C, Levis, B, Riehm, K E, Saadat, N, Levis, A W, Azar, M, Rice, D B, Krishnan, A, Wu, Y, Sun, Y, Imran, M, Boruff, J, Cuijpers, P, Gilbody, S, Ioannidis, J P A, Kloda, L A, McMillan, D, Patten, S B, Shrier, I, Ziegelstein, R C, Akena, D H, Arroll, B, Ayalon, L, Baradaran, H R, Baron, M, Beraldi, A, Bombardier, C H, Butterworth, P, Carter, G, Chagas, M H N, Chan, J C N, Cholera, R, Clover, K, Conwell, Y, de Man-van Ginkel, J M, Fann, J R, Fischer, F H, Fung, D, Gelaye, B, Goodyear-Smith, F, Greeno, C G, Hall, B J, Harrison, P A, Härter, M, Hegerl, U, Hides, L, Hobfoll, S E, Hudson, M, Hyphantis, T N, Inagaki, M, Ismail, K, Jetté, N, Khamseh, M E, Kiely, K M, Kwan, Y, Lamers, F, Liu, S-I, Lotrakul, M, Loureiro, S R, Löwe, B, Marsh, L, McGuire, A, Mohd-Sidik, S, Munhoz, T N, Muramatsu, K, Osório, F L, Patel, V, Pence, B W, Persoons, P, Picardi, A, Reuter, K, Rooney, A G, da Silva Dos Santos, I S, Shaaban, J, Sidebottom, A, Simning, A, Stafford, L, Sung, S, Tan, P L L, Turner, A, van Weert, H C P M, White, J, Whooley, M A, Winkley, K, Yamada, M, Thombs, B D & Benedetti, A 2020, 'The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression : An Individual Participant Data Meta-Analysis', Psychotherapy and Psychosomatics, vol. 89, no. 1, pp. 25-37. https://doi.org/10.1159/000502294