Depression in advanced cancer - Assessment challenges and associations with disease load

Background: Patients with advanced cancer commonly experience multiple somatic symptoms and declining functioning. Some highly prevalent symptoms also overlap with diagnostic symptom criteria of depression. Thus, assessing depression in these patients can be challenging. We therefore investigated 1) the effect of different scoring methods of depressive symptoms on detecting depression, and 2) the relationship between disease load and depression amongst patients with advanced cancer. Methods: The sample included 969 patients in the European Palliative Care Research Collaborative-Computer Symptom Assessment Study (EPCRC-CSA). Inclusion criteria were: incurable metastatic/locally advanced cancer and;7-:' 18 years. Biomarkers and length of survival were registered from patient-records. Depression was assessed using the Patient Health Questionnaire (PHQ-9) and applying three scoringmethods: inclusive (algorithm scoring including the somatic symptom-criteria), exclusive (algorithm scoring excluding the somatic symptom-criteria) and sum-score (sum of all symptoms with a cut-off >= 8). Results: Depression prevalence rates varied according to scoring-method: inclusive 13.7%, exclusive 14.9% and sum-score 45.3%. Agreement between the algorithm scoring-methods was excellent (Kappa0.81), but low between the inclusive and sum scoring-methods (Kappa=0.32). Depression was significantly associated with more pain (OR-range: 1.09-1.19, p < 0.001-0.04) and lower performance status (KPS-score, OR-range=0.68-0.72, p'- 0.001) irrespective of scoring-method. Limitations: Depression was assessed using self-report, not clinical interviews. Conclusions: The scoring-method, not excluding somatic symptoms, had the greatest effect on assessment outcomes. Increasing pain and poorer than expected physical condition should alert clinicians to possible co-morbid depression. The large discrepancy in prevalence rates between scoring-methods reinforces the need for consensus and validation of depression definitions and assessment in populations with high disease load. (C) 2014 Elsevier By. All rights reserved.