A longitudinal study of symptom cluster latent profiles in ovarian cancer patients undergoing chemotherapy

Abstract

Background: This study aimed to identify distinct patterns within the symptom cluster of fatigue, pain, and sleep disturbance among ovarian cancer patients receiving chemotherapy, to determine the factors predicting these patterns and their impact on quality of life. Methods: The longitudinal study collected data from 151 ovarian cancer patients at three time points: before chemotherapy (T0), after the first chemotherapy cycle (T1), and following the completion of four cycles of chemotherapy (T2). Latent profile analysis and latent transition analysis were used to identify symptom patterns and evaluate changes in symptom patterns. A bias-adjusted three-step approach was utilized to examine predictor variables and distal outcomes associated with latent class membership. Results: Three symptom patterns emerged: “All Low,” “Moderate” (T0)/“Low pain and high sleep disturbance” (T1 and T2), and “All High.” Patients with lower educational attainment and higher levels of anxiety and depression were found to be at an elevated risk of belonging to the “All High” class. All quality-of-life domains showed significant differences among the three subgroups, following an “All Low” > “All High” pattern (p < 0.05). Membership in three classes remained relatively stable over time, with probabilities of 0.749 staying within their groups from T0 to T2. Conclusions: This study underscores the existence of a diverse and heterogeneous experience within the symptom cluster of fatigue, pain, and sleep disturbance among ovarian cancer patients. Importantly, these patterns were stable throughout chemotherapy. Recognizing and understanding these patterns can inform the development of targeted interventions to alleviate the burden of symptom clusters in this population.