BACKGROUND: The prognostic utility of self-administered depression scales in chronic kidney disease (CKD) independent of a clinician-based major depressive disorder (MDD) diagnosis is neither clearly established nor are the optimal cutoff scores for predicting outcomes. The overlap between symptoms of depression and chronic disease raises the question of whether a cutoff score on a depression scale can be substituted for a time-consuming diagnostic interview to prognosticate risk. METHODS: The 16-item Quick Inventory of Depression Symptomatology-Self Report scale (QIDS-SR16) was administered to 266 consecutive outpatients with non-dialysis CKD, followed prospectively for 12 months for an apriori composite outcome of death or dialysis or hospitalization. Association of QIDS-SR16 best cutoff score, determined by receiver/responder operating characteristics curves, with outcomes was investigated using survival analysis. The effect modification of an interview-based clinician MDD diagnosis on this association was ascertained. RESULTS: There were 126 composite events. A QIDS-SR16 cutoff ≥8 had the best prognostic accuracy, hazards ratio (HR) = 1.77, 95% CI 1.24-2.53, p = 0.002. This cutoff remained significantly associated with outcomes even after controlling for comorbidities, estimated glomerular filtration rate, hemoglobin and serum albumin, adjusted HR (aHR) = 1.80, 95% CI 1.23-2.62, p = 0.002, and performed similarly to a clinician-based MDD diagnosis (aHR = 1.72, 95% CI 1.14-2.68). Adjustment for MDD conferred the association of QIDS-SR16 with outcomes no longer significant. CONCLUSIONS: QIDS-SR16 cutoff ≥8 adds to the prognostic information available to practicing nephrologists during routine clinic visits from comorbidities and laboratory data. This cutoff score performs similar to a clinician diagnosis of MDD and provides a feasible and time-saving alternative to an interview-based MDD diagnosis for determining prognosis in CKD patients.
BACKGROUND: The prognostic utility of self-administered depression scales in chronic kidney disease (CKD) independent of a clinician-based major depressive disorder (MDD) diagnosis is neither clearly established nor are the optimal cutoff scores for predicting outcomes. The overlap between symptoms of depression and chronic disease raises the question of whether a cutoff score on a depression scale can be substituted for a time-consuming diagnostic interview to prognosticate risk. METHODS: The 16-item Quick Inventory of Depression Symptomatology-Self Report scale (QIDS-SR16) was administered to 266 consecutive outpatients with non-dialysis CKD, followed prospectively for 12 months for an apriori composite outcome of death or dialysis or hospitalization. Association of QIDS-SR16 best cutoff score, determined by receiver/responder operating characteristics curves, with outcomes was investigated using survival analysis. The effect modification of an interview-based clinician MDD diagnosis on this association was ascertained. RESULTS: There were 126 composite events. A QIDS-SR16 cutoff ≥8 had the best prognostic accuracy, hazards ratio (HR) = 1.77, 95% CI 1.24-2.53, p = 0.002. This cutoff remained significantly associated with outcomes even after controlling for comorbidities, estimated glomerular filtration rate, hemoglobin and serum albumin, adjusted HR (aHR) = 1.80, 95% CI 1.23-2.62, p = 0.002, and performed similarly to a clinician-based MDD diagnosis (aHR = 1.72, 95% CI 1.14-2.68). Adjustment for MDD conferred the association of QIDS-SR16 with outcomes no longer significant. CONCLUSIONS: QIDS-SR16 cutoff ≥8 adds to the prognostic information available to practicing nephrologists during routine clinic visits from comorbidities and laboratory data. This cutoff score performs similar to a clinician diagnosis of MDD and provides a feasible and time-saving alternative to an interview-based MDD diagnosis for determining prognosis in CKDpatients.
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Authors: S Susan Hedayati; L Parker Gregg; Thomas Carmody; Nishank Jain; Marisa Toups; A John Rush; Robert D Toto; Madhukar H Trivedi Journal: JAMA Date: 2017-11-21 Impact factor: 56.272