Patients with advanced cancer and depression report a significantly higher symptom burden than non-depressed patients

OBJECTIVE: Clinical observations indicate that patients with advanced cancer and depression report higher symptom burden than nondepressed patients. This is rarely examined empirically. Study aim was to investigate the association between self-reported depression disorder (DD) and symptoms in patients with advanced cancer controlled for prognostic factors. METHOD: The sample included 935 patients, mean age 62, 52% males, from an international multicentre observational study (European Palliative Care Research Collaborative - Computerised Symptom Assessment and Classification of Pain, Depression and Physical Function). DD was assessed by the Patient Health Questionnaire-9 and scored with Diagnostic and Statistical Manual of Mental Disorder-5 algorithm for major depressive disorder, excluding somatic symptoms. Symptom burden was assessed by summing scores on somatic Edmonton Symptom Assessment Scale (ESAS) symptoms, excluding depression, anxiety, and well-being. Item-by-item scores and symptom burden of those with and without DD were compared using nonparametric Mann-Whitney U tests. The relative importance of sociodemographic, medical, and prognostic factors and DD in predicting symptom burden was assessed by hierarchical, multiple regression analyses. Result Patients with DD reported significantly higher scores on ESAS items and a twofold higher symptom burden compared with those without. Factors associated with higher symptom burden were as follows. DIAGNOSIS: lung (β = 0.15, p < 0.001) or breast cancer (β = 0.08, p < 0.05); poorer prognosis: high C-reactive protein (β = 0.08, p < 0.05), lower Karnofsky Performance Status (β = -0.14, p < 0.001), and greater weight loss (β = -0.15, p < 0.001); taking opioids (β = 0.11, p < 0.01); and having DD (β = 0.23, p < 0.001). The full model explained 18% of the variance in symptom burden. DD explained 4.4% over and above that explained by all the other variables. Significance of results Depression in patients with advanced cancer is associated with higher symptom burden. These results encourage improved routines for identifying and treating those suffering from depression

Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine

In the field of predictive, preventive and personalised medicine, researchers are keen to identify novel and reliable ways to predict and diagnose disease, as well as to monitor patient response to therapeutic agents. In the last decade alone, the sensitivity of profiling technologies has undergone huge improvements in detection sensitivity, thus allowing quantification of minute samples, for example body fluids that were previously difficult to assay. As a consequence, there has been a huge increase in tear fluid investigation, predominantly in the field of ocular surface disease. As tears are a more accessible and less complex body fluid (than serum or plasma) and sampling is much less invasive, research is starting to focus on how disease processes affect the proteomic, lipidomic and metabolomic composition of the tear film. By determining compositional changes to tear profiles, crucial pathways in disease progression may be identified, allowing for more predictive and personalised therapy of the individual. This article will provide an overview of the various putative tear fluid biomarkers that have been identified to date, ranging from ocular surface disease and retinopathies to cancer and multiple sclerosis. Putative tear fluid biomarkers of ocular disorders, as well as the more recent field of systemic disease biomarkers, will be shown