Latent profile analysis for assessing symptom clusters in women with breast cancer

• Published in: Journal of cancer survivorship 2024-07
• Main Authors: Park, Jin-Hee, Chun, Mison, Bae, Sun Hyoung, Woo, Jeonghee, Chon, Eunae, Kim, Hee Jun
• Format: Article
• Language: English
• ISSN: 1932-2259; 1932-2267; 1932-2267
• DOI: 10.1007/s11764-024-01648-6

To identify symptom clusters among breast cancer survivors and investigate differences in health-related quality of life (HRQoL) and distress based on these discerned symptom clusters using latent profile analysis. We enrolled 655 adult breast cancer survivors aged 19 years and older, registered with the Cancer Survivor Integrated Supportive Center from May 2020 to July 2022. The study measured five symptoms-pain, fatigue, insomnia, anxiety, and depression-using a Visual Analogue Scale ranging from 0 to 10 points. Distress was measured using the National Comprehensive Cancer Network Distress Thermometer, with scores ranging from 0 to 10 points. HRQoL was determined using the EuroQol-5 Dimension questionnaire. Data analysis was conducted using the Jamovi and Mplus 8.8 software programs. The Cluster with Few Symptoms (46.8%) was the most common, whereas the Psychological Cluster with a very high degree of depression and anxiety accounted for 20.0%, and the Moderate symptom cluster with symptoms of 3 or more points accounted for 14.4%. Distress scores were relatively high in the Psychological Cluster and the Pain-Fatigue-Insomnia Cluster, and were lowest in the Cluster with Few Symptoms (F = 103.92, p