Symptom Clusters in Cancer Patients and Their Caregivers- a Longitudinal Study

Overview

The complexity of cancer patients' symptoms and health problems constitutes considerable distress and burden for patients and their family caregivers. To help them manage the illness effectively, there is a need to better understand the complexity of symptoms and symptom clusters in patients and caregivers. Therefore, the purpose of this research is to explore a set of important fundamental research questions to advance the scientific knowledge of cancer patients' and caregivers' symptoms, symptom clusters and health-related quality of life. The investigators will follow 500 cancer patients and their caregivers with repeated measures over 6 months to assess their symptoms, symptom clusters, and quality of life over time. Caregiver burden will also be examined in the caregivers.

The specific aims of the study, where we will follow 500 cancer patients and their caregivers with repeated measures over 6 months, are to: 1. Explore cancer patients' symptoms, symptom clusters and symptom changes over time; and identify subgroups of patients with different symptom clusters. 2. Identify genomic markers for the different patient subgroups. 3. Explore symptoms, symptom clusters and burden in caregivers of cancer patients. 4. Explore relationships between patients' and caregivers' symptoms, symptom clusters, quality of life and caregiver burden. Patients will be asked to complete questionnaires to collect demographic characteristics and self-reported medical history information, a general symptom inventory, specific measures of the symptoms of pain, sleep disturbance, fatigue, depression, functional status and quality of life. The patients' medical record will be reviewed for disease and treatment information. The caregivers will also be asked to complete questionnaires about a general symptom inventory, specific measures of the symptoms of pain, sleep disturbance, fatigue, depression, functional status, quality of life and caregiver burden. Data Analyses will be done to identify symptom clusters of the different symptoms, and to identify patient subgroups based on their symptom experience and quality of life. Variations in symptom clusters and quality of life over time will also be evaluated. Genetic analyses will also be done in the patients.