Identifying Longitudinal Trajectories of Quality of Life and Associated Risk and Protective Factors Among Cancer Patients

OBJECTIVE: The 7-item Functional Assessment of Cancer Therapy-General (FACT-G7) is a validated, brief measure of health-related quality of life (QoL) used in oncology settings. While many conceptualize QoL as a static trial endpoint, growing evidence underscores its dynamic nature over time to inform point-of-care interventions. Grounded in the Wilson and Cleary model, this study aims to (1) identify distinct trajectories of QoL over a 12-month period using FACT-G7, and (2) incorporate clinical, mental health, sociodemographic, and healthcare system related factors to uncover risk and protective factors that shape patients' QoL trajectories. METHODS: Using FACT-G7 scores over a 12-month period from a sample of 4104 cancer patients (aged 19-92, M = 60.50, SD = 12.95) receiving cancer treatment, growth mixture modeling was fitted to identify subgroups of QoL trajectories. Multinomial logistic regression was conducted to examine the predictors of class membership. RESULTS: Results revealed a three-class model provided optimal fit: high QoL (40.1%), average QoL (40.3%), and low QoL (19.6%). Psychosocial factors - particularly loneliness (OR = 1.70, 95% CI:1.35-2.13) and financial difficulties (OR = 1.47, 95% CI:1.27-1.71) - strongly predicted membership in the low QoL trajectory. Clinical factors, including comorbidities (Charlson Comorbidity Index; CCI) and symptom burden severity (PRO-CTCAE), were associated with poorer QoL trajectories, with insomnia and nausea demonstrating the strongest negative effects. Conversely, higher satisfaction with cancer care and cancer-related self-efficacy were protective factors associated with higher QoL trajectories. CONCLUSIONS: The findings identify modifiable risk and protective factors that can inform targeted early interventions to improve long-term QoL outcomes across the cancer care continuum.