The Accuracy of the Patient Health Questionnaire-9 (PHQ-9) Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-analysis

Details

• Alternative Title:
  Psychother Psychosom
• Personal Author:
  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 H. ; 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 ; 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. ; Santos, Iná S. ; Shaaban, Juwita ; Sidebottom, Abbey ; Simning, Adam ; Stafford, Lesley ; Sung, Sharon ; Tan, Pei Lin Lynnette ; Turner, Alyna ; van Weert, Henk C. ; White, Jennifer ; Whooley, Mary A. ; Winkley, Kirsty ; Yamada, Mitsuhiko ; Thombs, Brett D. ; Benedetti, Andrea
• 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 individual participant data meta-analysis (IPDMA) 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 & Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000 – 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 to 0.24 lower compared to fully structured interviews and 0.06 to 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.
  
  
• Subjects:
  Algorithms Data Accuracy Depressive Disorder, Major Humans Mass Screening Patient Health Questionnaire Psychiatric Status Rating Scales Sensitivity And Specificity
• Keywords:
  Depression Diagnostic Accuracy Meta-analysis Patient Health Questionnaire-9 Screening
• Source:
  Psychother Psychosom. 89(1):25-37
• Pubmed ID:
  31593971
• Pubmed Central ID:
  PMC6960351
• Document Type:
  Journal Article
• Funding:
  R36 HS018246/HS/AHRQ HHSUnited States/ ; R34 MH072925/MH/NIMH NIH HHSUnited States/ ; R01 MH069666/MH/NIMH NIH HHSUnited States/ ; R01 MH073687/MH/NIMH NIH HHSUnited States/ ; TL1 RR024135/RR/NCRR NIH HHSUnited States/ ; MR/J000914/1/MRC_/Medical Research CouncilUnited Kingdom/ ; F30 MH096664/MH/NIMH NIH HHSUnited States/ ; MRF_C0396/MRF/MRFUnited Kingdom/ ; R01 HL079235/HL/NHLBI NIH HHSUnited States/ ; R49 CE002093/CE/NCIPC CDC HHSUnited States/ ; R34 MH084673/MH/NIMH NIH HHSUnited States/ ; P30 DK050456/DK/NIDDK NIH HHSUnited States/ ; T37 MD001449/MD/NIMHD NIH HHSUnited States/ ; T32 GM007356/GM/NIGMS NIH HHSUnited States/ ; K02 MH065919/MH/NIMH NIH HHSUnited States/ ; R24 MH071604/MH/NIMH NIH HHSUnited States/
• Volume:
  89
• Issue:
  1
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:219b5f160c592ab55f74c86101f3c02dd80ec4ac6031a2b846bf6ce0c6c6470b37174d65b5832dbd12032335ec37e753092b41c2eeac29d15d1e95b24c118c9b
• Download URL:
  https://stacks.cdc.gov/view/cdc/84332/cdc_84332_DS1.pdf
• File Type:
  [PDF - 369.31 KB ]