The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual...

Area of Science:

• Psychiatry and Mental Health
• Diagnostic Accuracy Studies
• Epidemiology of Mental Disorders

Background:

• The Patient Health Questionnaire-9 (PHQ-9) is a widely used tool for screening major depression.
• Screening can be performed using a cutoff score (e.g., ≥10) or a diagnostic algorithm.
• Previous meta-analyses have limitations in scope and methodology.

Purpose of the Study:

• To conduct an individual participant data meta-analysis to evaluate the diagnostic accuracy of two PHQ-9 algorithms.
• To compare the accuracy of PHQ-9 algorithms against the standard PHQ-9 cutoff score of ≥10.
• To assess the performance of PHQ-9 screening methods across different reference standards.

Main Methods:

• An individual participant data meta-analysis was performed.
• Searched Medline, PsycINFO, and Web of Science databases (2000-2015).
• Included studies with major depression status determined by a validated diagnostic interview.

Main Results:

• Data from 54 studies (16,688 participants, 2,091 cases) were analyzed.
• For semi-structured interviews, pooled sensitivity/specificity for algorithms were 0.57/0.95 (original) and 0.61/0.95 (modified).
• The PHQ-9 cutoff score of ≥10 showed higher sensitivity (0.88) and specificity (0.86) compared to algorithms when using semi-structured interviews.

Conclusions:

• The PHQ-9 cutoff score approach (≥10) is more accurate for detecting major depression than PHQ-9 diagnostic algorithms.
• The findings support the use of the cutoff score method for more reliable depression screening.
• Algorithm performance varied depending on the reference diagnostic interview standard.