Symptom cluster research: conceptual, design, measurement, and analysis issues

Cancer patients may experience multiple concurrent symptoms caused by the cancer, cancer treatment, or their combination. The complex relationships between and among symptoms, as well as the clinical antecedents and consequences, have not been well described. This paper examines the literature on cancer symptom clusters focusing on the conceptualization, design, measurement, and analytic issues. The investigation of symptom clustering is in an early stage of testing empirically whether the characteristics defined in the conceptual definition can be observed in cancer patients. Decisions related to study design include sample selection, the timing of symptom measures, and the characteristics of symptom interventions. For self-report symptom measures, decisions include symptom dimensions to evaluate, methods of scaling symptoms, and the time frame of responses. Analytic decisions may focus on the application of factor analysis, cluster analysis, and path models. Studying the complex symptoms of oncology patients will yield increased understanding of the patterns of association, interaction, and synergy of symptoms that produce specific clinical outcomes. It will also provide a scientific basis and new directions for clinical assessment and intervention.