BACKGROUND Fatigue is a major disease and treatment burden for cancer patients. Several scales have been created to measure fatigue, but many are long and difficult for very ill patients to complete, or they are not easy to translate for non‐English speaking patients. The Brief Fatigue Inventory was developed for the rapid assessment of fatigue severity for use in both clinical screening and clinical trials. METHODS The study enrolled 305 consecutive, consenting adult inpatients and outpatients with cancer who could understand and complete the self‐report measures used in the study. The same instruments also were administered to 290 community‐dwelling adults to obtain a comparison sample. Research staff completed a form that indicated the primary site and stage of the cancer, rated the Eastern Cooperative Oncology Group performance status of the patient, described the characteristics of the pain, and described the current pain treatment being provided to the patients. RESULTS The BFI was shown to be an internally stable (reliable) measure that tapped a single dimension, best interpreted as severity of fatigue. It correlated highly with similar fatigue measures. Greater than 98% of patients were able to complete it. A range of scores defining severe fatigue was identified. CONCLUSIONS The BFI is a reliable instrument that allows for the rapid assessment of fatigue level in cancer patients and identifies those patients with severe fatigue. Cancer 1999;85:1186–96. © 1999 American Cancer Society.

Background We performed a prospective longitudinal study to profile patient-reported symptoms during radiation therapy (RT) or concurrent chemoradiation (CCRT) for head and neck cancer. The goals were to understand the onset and trajectory of specific symptoms and their severity, identify clusters, and to facilitate symptom interventions and clinical trial design. Methods Participants in this questionnaire-based study received RT or CCRT. They completed the MD Anderson Symptom Inventory—Head and Neck Module before and weekly during treatment. Symptom scores were compared between treatment groups, and hierarchical cluster analysis was used to depict clustering of symptoms at treatment end. Variables thought to predict symptom severity were assessed using a multivariate mixed model. Results Among the 149 patients studied, most (47%) had oropharyngeal tumors, and nearly half received CCRT. Overall symptom severity (P<0.001) and symptom interference (P<0.0001) became progressively more severe and were more severe for those receiving CCRT. On multivariate analysis, baseline performance status (P<0.001) and receipt of CCRT (P<0.04) correlated with higher symptom severity. Fatigue, drowsiness, lack of appetite, problem with mouth/throat mucus, and problem tasting food were more severe for those receiving CCRT. Both local and systemic symptom clusters were identified. Conclusions Our findings from this prospective longitudinal study identified a pattern of local and systemic symptoms, symptom clusters, and symptom interference that was temporally distinct and marked by increased magnitude and a shift in individual symptom rank order during the treatment course. These inform us about symptom intervention needs, and are a benchmark for future symptom intervention clinical trials.

A B S T R A C TBackground. Pain and fatigue are common debilitating symptoms reported by both patient and community-dwelling populations. However, population-based studies typically focus on psychosocial variables as correlates of fatigue, with little effort toward assessing pain as a risk factor. This study examines the specific relationship between pain and fatigue and the importance of mood and sleep as covariates of fatigue in a community-dwelling sample of adults. We also assessed the prevalence of mild, moderate, and severe fatigue for this sample.Methods. Data were collected using self-administered questionnaires assessing demographic characteristics and symptoms, including pain, fatigue, mood, and sleep disturbance, in a sample (N = 274) of community-dwelling adults.Results. Regression analyses showed pain, mood, and sleep as significantly associated with fatigue, with pain being the most highly correlated. However, while pain accounted for the largest proportion of the variability in fatigue, mood modified the relationship between pain and fatigue. We also found that 9% of the sample reported no fatigue, 41% reported mild fatigue, 42% reported moderate fatigue, and 8% reported severe fatigue.Conclusions. Our findings provide empirical support of the importance of assessing pain as an important risk factor of fatigue and examining mood as a covariate in population-based studies of fatigue.