Key result
A 4-item PHQ-9 subscale detects depressive disorder with an AUC of ~0.94.
Why the study?
Depressive disorder detection in elderly patients with chronic physical diseases lacks identification of specific depressive symptom profiles and optimal PHQ-9 cut-off sub-scores.
Cross-Sectional (n=231)
No
Effect estimate: AUC 0.937
p-value: p=<0.001
May support efficient depression screening; leaves open prospective validation and outcome impact in clinical practice.
OBJECTIVE: We aimed to identify depressive symptom profiles that indicated the presence of depressive disorder and present optimal cut-off sub-scores for depressive symptom profiles for detecting depressive disorder in elderly subjects with chronic physical diseases including diabetes, chronic obstructive pulmonary disease/asthma, and coronary artery disease, using the Patient Health Questionnaire-9 (PHQ-9). METHODS: Two hundred and thirty-one elderly patients with chronic physical diseases were recruited consecutively from a university-affiliated general hospital in South Korea. RESULTS: Greater severities of all 9 depressive symptoms in the PHQ-9 were presented in those with depressive disorder rather than those without depressive disorder. A binary logistic regression modeling presented that little interest [adjusted odds ratio (aOR)=4.648, p<0.001], reduced/increased sleep (aOR=3.269, p<0.001), psychomotor retardation/agitation (aOR=2.243, p=0.004), and concentration problem (aOR=16.116, p<0.001) were independently associated with increased likelihood of having depressive disorder. Receiver operating characteristics (ROC) curve analysis presented that the optimal cut-off value of score on the items for little interest, reduced/increased sleep, psychomotor retardation/agitation and concentration problem (PHQ-9) for detecting depressive disorder was 4 with 61.9% of sensitivity and 91.5% of specificity [area under curve (AUC)=0.937, p<0.001]. CONCLUSION: Our findings suggested that the diagnostic weighting of little interest, reduced/increased sleep, psychomotor retardation/agitation, and concentration problem is needed to detect depressive disorder among the elderly patients with chronic physical diseases.
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Park et al. (2017) conducted a cross-sectional in Depressive disorder in chronic physical diseases (n=231). 4-item PHQ-9 subscale (little interest, sleep, psychomotor, concentration) vs. HAMD diagnosis of depressive disorder was evaluated on Detection of depressive disorder (AUC) (AUC 0.937, p=<0.001). A 4-item subscale of the PHQ-9 (little interest, sleep, psychomotor changes, and concentration) with a cut-off score of 4 detected depressive disorder with an AUC of 0.937, 61.9% sensitivity, and 91.5% specificity.
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