A latent profile analysis to assess physical, cognitive and emotional symptom clusters in women with breast cancer

Abstract

Objective Current research on the physical and psychological functioning of breast cancer survivors often takes an approach where symptoms are studied independently even though they often occur in clusters This paper aims to identify physical and psychological symptom clusters among breast cancer survivors while assessing clinical, psychosocial and demographic characteristics that predict subgroup membership. Design Using post-surgical data collected from 240 women with stage 0–III breast cancer, symptom clusters were identified using latent profile analysis of patient-reported symptoms. Main Outcome Measures Baseline measures included the Pittsburg Sleep Quality Index, the Fatigue Symptom Inventory, the Hamilton Rating Scales for depression and anxiety and the Impact of Event Scale. Results Three distinct classes were identified: (1) mild physical, cognitive and emotional symptoms, (2) moderate across all domains and (3) high levels of all symptoms. Lower socio-economic status, minority ethnicity, younger age, advanced disease stage along with lower self-efficacy and less internal locus of control were significantly associated with a higher likelihood of class 3 membership. Conclusion By identifying those most at risk for severe physical and psychological symptoms in the post-surgical period, our results can guide the development of tailored interventions to optimise quality of life during breast cancer treatment.