![]() ![]() The most often used and recommended questionnaires for the oncological setting are the Hospital Anxiety and Depression Scale (HADS) ( Zigmond & Snaith, 1983), the Patient Health Questionnaire (PHQ-9) ( Kroenke et al., 2001), the Beck Depression Inventory (BDI-II) ( Beck et al., 1996) and the Center for Epidemiologic Studies Depression Scale (CES-D) ( Radloff, 1977). Additionally, the selection of self-reported measures should be based on existing validation data in the population of interest ( Ziegler et al., 2011). When used appropriately, such instruments are a cost-effective and equitable means of identifying depressive symptoms, much less time and resource consuming than structured interviews ( Vodermaier et al., 2009 Wakefield et al., 2015). The validation of self-reported measures of depression is an important contribution to this field. These recommendations highlight the use of standardized measures, validated for oncological populations, with several depression assessment tools proving to be effective in this context. To address this need, the National Comprehensive Cancer Network (NCCN) ( National Institute for Clinical Excellence et al., 2004) and the American Society of Clinical Oncology (ASCO) ( Andersen et al., 2014) have published guidelines emphasizing the importance of formally assessing depressive symptoms regularly across the trajectory of care. While prevalence over the first five years following a cancer diagnosis ( Mitchell et al., 2011 Pitman et al., 2018) may range from 4% to 20%, depression remains under-diagnosed and is often left untreated in patients with cancer ( Walker et al., 2014), calling for an urgent identification of appropriate screening and assessment tools for use in routine clinical practice in this field. The reported prevalence of depression in patients with cancer varies according to the type and clinical characteristics of cancer, the conceptualization of depression, and the criteria and methods that are used for diagnosis ( Massie, 2004). Patients with cancer frequently experience symptoms of depression, which can negatively affect long-term quality of life, treatment compliance, health service use, and mortality ( Andersen et al., 2014 Chida et al., 2008). Exclusion of somatic items did not affect screening accuracy. The BDI-II demonstrated good psychometric properties in patients with cancer, comparable to a population without cancer. A good criterion validity for BDI-II was also obtained in the non-oncological population (AUC = 0.87 95% CI 0.81–0.91), with a cut-off of 18 (sensitivity=84% specificity=73%). Excluding somatic items did not significantly change the ROC curve for BDI-II (difference AUCs = 0.002, p=0.9). A cut-off score of 14 had sensitivity of 87% and specificity of 73%. Criterion validity was good for detecting depression in oncological patients, with an area under the ROC curve (AUC) of 0.85 (95% confidence interval, 0.76–0.91). ![]() ResultsĬonfirmatory factor analysis suggested a three-factor structure model (cognitive, affective and somatic) provided best fit to data in both samples. Psychometric properties of the BDI-II Portuguese version were assessed separately in 202 patients with cancer, and 376 outpatients with mental health complaints but without cancer. Methodĭata was obtained in an outpatient neuropsychiatry unit treating patients with and without cancer. We assessed validity of the Beck Depression Inventory (BDI-II) in this population. Screening for depression in patients with cancer can be difficult due to overlap between symptoms of depression and cancer. ![]()
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