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 ≥ 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 scoring-methods: 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 (Kappa = 0.81), 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.