The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
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
Аннотация
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.