title: Case identification of depression in patients with chronic physical health problems: a diagnostic accuracy meta-analysis of 113 studies.
abstract: BACKGROUND
  Depression is more likely in patients with chronic physical illness, and is associated with increased rates of disability and mortality. Effective treatment of depression may reduce morbidity and mortality. The use of two stem questions for case finding in diabetes and coronary heart disease is advocated in the Quality and Outcomes Framework, and has become normalised into primary care.
  
  
  OBJECTIVE
  To define the most effective tool for use in consultations to detect depression in people with chronic physical illness.
  
  
  METHODS
  Meta-analysis.
  
  
  METHODS
  The following data sources were searched: CENTRAL, CINAHL, Embase, HMIC, MEDLINE, PsycINFO, Web of Knowledge, from inception to July 2009. Three authors selected studies that examined identification tools and used an interview-based ICD (International Classification of Diseases) or DSM (Diagnostic and statistical Manual of Mental Disorders) diagnosis of depression as reference standard. At least two authors independently extracted study characteristics and outcome data and assessed methodological quality.
  
  
  RESULTS
  A total of 113 studies met the eligibility criteria, providing data on 20,826 participants. It was found that two stem questions, PHQ-9 (Patient Health Questionnaire), the Zung, and GHQ-28 (General Health Questionnaire) were the optimal measures for case identification, but no method was sufficiently accurate to recommend as a definitive case-finding tool. Limitations were the moderate-to-high heterogeneity for most scales and the facts that few studies used ICD diagnoses as the reference standard, and that a variety of methods were used to determine DSM diagnoses.
  
  
  CONCLUSIONS
  Assessing both validity and ease of use, the two stem questions are the preferred method. However, clinicians should not rely on the two-questions approach alone, but should be confident to engage in a more detailed clinical assessment of patients who score positively.
authors.affiliation: National Collaborating Centre for Mental Health, London. nmeader@hotmail.com
authors.forename: Nicholas
authors.initials: N
authors.lastname: Meader
authors.forename: Alex J
authors.initials: AJ
authors.lastname: Mitchell
authors.forename: Carolyn
authors.initials: C
authors.lastname: Chew-Graham
authors.forename: David
authors.initials: D
authors.lastname: Goldberg
authors.forename: Maria
authors.initials: M
authors.lastname: Rizzo
authors.forename: Victoria
authors.initials: V
authors.lastname: Bird
authors.forename: David
authors.initials: D
authors.lastname: Kessler
authors.forename: Jon
authors.initials: J
authors.lastname: Packham
authors.forename: Mark
authors.initials: M
authors.lastname: Haddad
authors.forename: Stephen
authors.initials: S
authors.lastname: Pilling
mesh_terms: D019540:Area Under Curve; D001499:Bayes Theorem; D002908:Chronic Disease / Q000523:psychology*; D003866:Depressive Disorder / Q000175:diagnosis*; D058006:General Practice / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D011569:Psychiatric Status Rating Scales / Q000592:standards*; D012680:Sensitivity and Specificity; D011795:Surveys and Questionnaires