scholarly journals Screening for Depression in Medical Settings with the Patient Health Questionnaire (PHQ): A Diagnostic Meta-Analysis

2007 ◽  
Vol 22 (11) ◽  
pp. 1596-1602 ◽  
Author(s):  
Simon Gilbody ◽  
David Richards ◽  
Stephen Brealey ◽  
Catherine Hewitt
Keyword(s):  
Meta Analysis ◽  
Patient Health Questionnaire ◽  
Health Questionnaire ◽  
Medical Settings ◽  
Patient Health

scholarly journals Case finding and screening clinical utility of the Patient Health Questionnaire (PHQ-9 and PHQ-2) for depression in primary care: a diagnostic meta-analysis of 40 studies

BJPsych Open ◽  
2016 ◽  
Vol 2 (2) ◽  
pp. 127-138 ◽  
Author(s):  
Alex J. Mitchell ◽  
Motahare Yadegarfar ◽  
John Gill ◽  
Brendon Stubbs
Keyword(s):  
Primary Care ◽  
Clinical Utility ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Case Finding ◽  
Classification Systems ◽  
Patient Health Questionnaire ◽  
Health Questionnaire ◽  
Scoring Method ◽  
Patient Health

BackgroundThe Patient Health Questionnaire (PHQ) is the most commonly used measure to screen for depression in primary care but there is still lack of clarity about its accuracy and optimal scoring method.AimsTo determine via meta-analysis the diagnostic accuracy of the PHQ-9-linear, PHQ-9-algorithm and PHQ-2 questions to detect major depressive disorder (MDD) among adults.MethodWe systematically searched major electronic databases from inception until June 2015. Articles were included that reported the accuracy of PHQ-9 or PHQ-2 questions for diagnosing MDD in primary care defined according to standard classification systems. We carried out a meta-analysis, meta-regression, moderator and sensitivity analysis.ResultsOverall, 26 publications reporting on 40 individual studies were included representing 26 902 people (median 502, s.d.=693.7) including 14 760 unique adults of whom 14.3% had MDD. The methodological quality of the included articles was acceptable. The meta-analytic area under the receiver operating characteristic curve of the PHQ-9-linear and the PHQ-2 was significantly higher than the PHQ-9-algorithm, a difference that was maintained in head-to-head meta-analysis of studies. Our best estimates of sensitivity and specificity were 81.3% (95% CI 71.6–89.3) and 85.3% (95% CI 81.0–89.1), 56.8% (95% CI 41.2–71.8) and 93.3% (95% CI 87.5–97.3) and 89.3% (95% CI 81.5–95.1) and 75.9% (95% CI 70.1–81.3) for the PHQ-9-linear, PHQ-9-algorithm and PHQ-2 respectively. For case finding (ruling in a diagnosis), none of the methods were suitable but for screening (ruling out non-cases), all methods were encouraging with good clinical utility, although the cut-off threshold must be carefully chosen.ConclusionsThe PHQ can be used as an initial first step assessment in primary care and the PHQ-2 is adequate for this purpose with good acceptability. However, neither the PHQ-2 nor the PHQ-9 can be used to confirm a clinical diagnosis (case finding).

scholarly journals Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis

BMJ ◽  
2019 ◽  
pp. l1476 ◽  
Author(s):  
Brooke Levis ◽  
Andrea Benedetti ◽  
Brett D Thombs
Keyword(s):  
Major Depression ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Patient Health Questionnaire ◽  
Individual Participant Data ◽  
Health Questionnaire ◽  
Structured Interviews ◽  
Diagnostic Interviews ◽  
Patient Health ◽  
Individual Participant

Abstract Objective To determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression. Design Individual participant data meta-analysis. Data sources Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-February 2015). Inclusion criteria Eligible studies compared PHQ-9 scores with major depression diagnoses from validated diagnostic interviews. Primary study data and study level data extracted from primary reports were synthesized. For PHQ-9 cut-off scores 5-15, bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, among studies that used semistructured diagnostic interviews, which are designed for administration by clinicians; fully structured interviews, which are designed for lay administration; and the Mini International Neuropsychiatric (MINI) diagnostic interviews, a brief fully structured interview. Sensitivity and specificity were examined among participant subgroups and, separately, using meta-regression, considering all subgroup variables in a single model. Results Data were obtained for 58 of 72 eligible studies (total n=17 357; major depression cases n=2312). Combined sensitivity and specificity was maximized at a cut-off score of 10 or above among studies using a semistructured interview (29 studies, 6725 participants; sensitivity 0.88, 95% confidence interval 0.83 to 0.92; specificity 0.85, 0.82 to 0.88). Across cut-off scores 5-15, sensitivity with semistructured interviews was 5-22% higher than for fully structured interviews (MINI excluded; 14 studies, 7680 participants) and 2-15% higher than for the MINI (15 studies, 2952 participants). Specificity was similar across diagnostic interviews. The PHQ-9 seems to be similarly sensitive but may be less specific for younger patients than for older patients; a cut-off score of 10 or above can be used regardless of age.. Conclusions PHQ-9 sensitivity compared with semistructured diagnostic interviews was greater than in previous conventional meta-analyses that combined reference standards. A cut-off score of 10 or above maximized combined sensitivity and specificity overall and for subgroups. Registration PROSPERO CRD42014010673.

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