Abstract

The National Institute of Mental Health Affective Disorders Workgroup identified the assessment of an individual's burden of illness as an important need. The Individual Burden of Illness Index for Depression (IBI-D) metric was developed to meet this need. To assess the use of the IBI-D for multidimensional assessment of treatment efficacy for depressed patients. Complete data on depressive symptom severity, functioning, and quality of life (QOL) from depressed patients (N = 2280) at entry and exit of level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study (12-week citalopram treatment) were used as the basis for calculating IBI-D and self-rating scale changes. Principal component analysis of patient responses at the end of level 1 of STAR*D yielded a single principal component, IBI-D, with a nearly identical eigenvector to that previously reported. While changes in symptom severity (Quick Inventory of Depressive Symptomatology-Self Report) accounted for only 50% of the variance in changes in QOL (Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form) and 47% of the variance in changes in functioning (Work and Social Adjustment Scale), changes in IBI-D captured 83% of the variance in changes in QOL and 80% in functioning, while also capturing 79% of the variance in change in symptom severity (Quick Inventory of Depressive Symptomatology-Self Report). Most importantly, the changes in IBI-D of the 36.6% of remitters who had abnormal QOL and/or functioning (mean [SD], 2.98 [0.35]) were significantly less than the changes in IBI-D of those who reported normal QOL and functioning (IBI-D = 1.97; t = 32.6; P < 10(-8)) with an effect size of a Cohen d of 2.58. In contrast, differences in symptom severity, while significant, had a Cohen d of only 0.78. Remission in depressed patients, as defined by a reduction in symptom severity, does not denote normal QOL or functioning. By incorporating multidimensional patient-reported outcomes, the IBI-D provides a single measure that adequately captures the full burden of illness in depression both prior to and following treatment; therefore, it offers a more accurate metric of recovery. clinicaltrials.gov Identifier: NCT00021528.

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