Exercise, Nutrition, and Palliative Care in Advanced Lung Cancer (ENPAL)

Background: Evidence supports exercise and nutrition as beneficial for enhancing QOL in earlier stages of lung cancer; however, there is minimal research of either intervention - and none with combined interventions - in advanced lung cancer patients. In addition to a multimodal intervention approach that includes nutrition and exercise, consideration of advanced cancer care symptom management is crucial for optimizing the potential benefits of either intervention. Objectives: Primary outcome measure of this study is feasibility, including recruitment (% who participate from those eligible), attendance (weekly group class), assessment completion, safety (adverse event reporting), attrition rates, and qualitative themes generated from one-on-one participant interviews. The secondary outcome to be measured is the impact of the intervention on PROs, including QOL, fatigue and symptom burden, as well as self-reported physical activity levels and physical function assessed in-person. Methods: The proposed exercise intervention will include a centre-based group exercise program plus home-based exercises, and behaviour change support for advanced non-small cell lung cancer (NSCLC) patients, classified as stage III or IV with self-reported symptom burden. Eligible participants must be cleared by the health care professionals (HCP) to engage in mild to moderate levels of physical activity (PA). Using a prospective, mixed-methods design (supported by the Medical Research Council guidance for the evaluation of complex interventions), the quantitative component of this pilot study will measure feasibility and exploratory outcome measures, with an embedded qualitative component to examine participant perspectives about study tolerability/feasibility of the intervention. A subset of participants and instructors will be recruited for qualitative interviews using purposive sampling to achieve maximum variation based on factors that may lead to different viewpoints (e.g., age, gen