A205: What are the treatment-related preferences of patients with advanced cancer? A discrete choice experiment
1University of Leeds, Leeds, UK,2Leeds Teaching Hospitals NHS Trust, Leeds, UK
It is of growing importance that clinicians understand the perspectives and preferences of their patients, in order to provide them with relevant information and to facilitate their treatment decisions. A discrete choice experiment (DCE) assesses preferences for multiple attributes of different options simultaneously and we have used it to evaluate patient preferences for the treatment of advanced cancer.
This exploratory DCE study investigated the factors that influence upper gastro-intestinal cancer patients' treatment decisions by quantifying the trade-offs between the following treatment attributes: life expectancy, number of hospital visits, nausea, diarrhoea and fatigue. The study questionnaires were distributed amongst consented patients at oncology clinics at St James's University Hospital from April to October 2014 and 36 responses were collected.
The treatment options featuring severe diarrhoea (coefficient = -1.57 [p = 0.001]) and severe fatigue (-1.06 [p=0.014]) were chosen less frequently than the treatment options featuring milder forms of diarrhoea (-0.48 [p=0.172]) or fatigue (-0.30 [p=0.397]). Patients were willing to forgo life expectancy in order to avoid the following side effects: severe diarrhoea (17.67 months), severe fatigue (16.36), severe nausea (5.46) and moderate diarrhoea (4.83).
Our results indicated that patients with UGI cancer will trade off some additional life expectancy in order to avoid treatment side effects, particularly diarrhoea and fatigue. The conclusions we can draw from our results are limited to the small sample size and therefore lack of statistically significant results. Despite this, our findings should be of interest to all stakeholders in cancer treatment, including patients, clinicians, healthcare researchers and those who design healthcare policy or guidance. Furthermore, this study contributes to growing body of research in health economics that shows the DCE to be an effective model for measuring patient treatment preferences.