Symptom Clusters in Breast Cancer Survivors: A Latent Class Profile Analysis

OBJECTIVES: To identify symptom clusters in breast cancer survivors and to determine sociodemographic and clinical characteristics influencing symptom cluster membership. SAMPLE AND SETTING: The authors performed a cross-sectional secondary analysis of data obtained from a community-based cancer registry-linked survey with 1,500 breast cancer survivors 6-13 months following a breast cancer diagnosis. METHODS AND VARIABLES: Symptom clusters were identified using latent class profile analysis of four patient-reported symptoms (pain, fatigue, sleep disturbance, and depression) with custom PROMIS® short forms. RESULTS: Four distinct classes were identified. IMPLICATIONS FOR NURSING: Common symptom clusters may lead to better prevention and treatment strategies that target a group of symptoms. Results also suggest that certain factors place patients at high risk for symptom burden, which can guide tailored interventions.