title: Cancer symptom clusters:  current concepts and controversies.
abstract: OBJECTIVE
  Cluster research examines complex interrelationships between multiple concurrent symptoms and their mechanisms. An individual's varying understanding of the cluster concept and variations in assessment tools results in discrepancies. This article will focus on the conceptual and methodological issues associated with definitions, symptom interrelationships, and outcomes of cancer symptom clusters.
  
  
  RESULTS
  An important issue in symptom cluster research is to clarify the definition of a cluster. Some evidence suggests that 'symptom pairs' should be treated as clusters. There is substantial evidence (both qualitative and quantitative) to support a psychoneurological symptom cluster in cancer patients. It has been proposed that consistent clusters are those that have similar 'core' symptoms over time. Research has also shown that a 'sentinel' symptom can predict the presence of other relevant symptoms within a cluster. Identification of patient subgroups with higher symptom severity may be useful in targeting the most needy individuals for intervention. Symptom clusters are predictors of patient outcomes, including decreased functional performance and shorter cancer survival.
  
  
  CONCLUSIONS
  Additional efforts should refine the cluster definition and elucidate the cluster stability and sentinel symptom. Both conceptual and empirical contributions should advance symptom cluster research. The qualitative approaches can explore the experience of symptom clusters and provide a conceptual basis for future research.
authors.affiliation: Department of Solid Tumor Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA. aktasa@ccf.org
authors.forename: Aynur
authors.initials: A
authors.lastname: Aktas
mesh_terms: D035843:Biomedical Research / Q000379:methods* / Q000639:trends; D015340:Epidemiologic Research Design; D005163:Factor Analysis, Statistical; D006801:Humans; D008495:Medical Oncology / Q000379:methods* / Q000639:trends; D015233:Models, Statistical; D009369:Neoplasms / Q000150:complications / Q000503:physiopathology*; D039781:PubMed; D012044:Regression Analysis; D013577:Syndrome