Parsing Depression From Fatigue in Patients with Cancer Using the Fatigue Symptom Inventory

ContextA central aim in the management of cancer-related fatigue (CRF) is to identify treatable causes, such as depression. However, CRF and depression symptoms overlap and frequently co-occur, complicating diagnostic assessment.ObjectivesAs cancer-related symptoms have been associated with more functional impairment among patients who are depressed, this study tested the ratio of fatigue interference to fatigue severity as a method for identifying depression cases. Patients who reported that interference was greater than severity were expected to show higher rates of depression as measured by self-report instrument or structured interview.MethodsA secondary analysis was conducted using data from patients who were attending a hospital thoracic oncology clinic and who completed the Fatigue Symptom Inventory (FSI) and Hospital Anxiety and Depression Scale (Sample 1, n = 86). Analyses were then replicated in a sample of diverse cancer patients who completed the FSI and a structured clinical interview for depression on presentation to a CRF clinic at the same hospital (Sample 2, n = 39).ResultsReceiver operating curve analyses supported use of the FSI interference/severity ratio in distinguishing depression cases and noncases (area under the curve: Sample 1 = 0.84, 95% confidence interval [CI] 0.74–0.94; Sample 2 = 0.87, 95% CI 0.76–0.99). With sensitivity and specificity weighted equally, the optimal cutoff was ≥1.0 in Sample 1 (sensitivity = 62.5%, specificity = 91.4%) and Sample 2 (sensitivity = 90.9%, specificity = 85.7%).ConclusionA fatigue score pattern in which interference was greater than or equal to severity predicted depression in two patient samples. This ratio may be useful for brief initial screening of depression in the context of fatigue.