Identification of Latent Classes Based on Prespecified Symptom Cluster in Posttreatment Cancer Survivors

BACKGROUND: Cancer-related symptoms often occur in clusters; however, survivorship care remains largely symptom-specific, limiting oncology nurses' ability to assess and manage co-occurring symptoms comprehensively. OBJECTIVE: In this study, we aimed to identify latent classes based on a prespecified symptom cluster (pain, fatigue, depressive symptoms, and sleep disturbance) among posttreatment cancer survivors, examine factors associated with class membership, and compare health-related quality of life (HRQOL) across classes. METHODS: This secondary cross-sectional analysis used online survey data from 5 cancer survivor communities in South Korea. The sample included 1019 posttreatment survivors of breast, colorectal, lung, stomach, or thyroid cancer. Symptoms were assessed using the survivorship concerns checklist from the National Comprehensive Cancer Network Guidelines for Cancer Survivorship, and HRQOL was measured using the Korean version of the EORTC QLQ-C30. Latent class analysis identified symptom cluster classes. RESULTS: Three latent classes were identified. Class 1 showed a high probability of all symptoms (34.3%). Class 2 showed a high probability of pain and a moderate probability of sleep disturbance (19.8%). Class 3 showed a low probability of all symptoms (45.9%). Older age, lower income, stomach cancer diagnosis, and multimodal treatment increased the likelihood of membership in classes 1 and 2, whereas adherence to a healthy diet decreased this likelihood. HRQOL differed significantly across classes, with class 1 showing the poorest outcomes. CONCLUSIONS: Distinct latent classes revealed substantial heterogeneity in symptom experience and HRQOL among posttreatment cancer survivors. IMPLICATIONS FOR PRACTICE: Findings support risk-stratified, symptom cluster-based survivorship care to improve HRQOL.