Sleep Disturbance in Breast Cancer Under Chemotherapy: A Multifactorial Analysis Emphasizing Psychosocial Dimensions

Background: Sleep disturbance is highly prevalent among cancer patients and has been associated with poorer quality of life and potentially adverse oncologic outcomes. Breast cancer patients undergoing chemotherapy are particularly vulnerable due to overlapping physiological, psychological, and treatment-related stressors. This study aimed to determine the prevalence of sleep disturbances and to identify associated clinical and psychosocial factors in this patient population. Methods: A total of 231 breast cancer patients receiving chemotherapy were evaluated. Data on demographic characteristics, menopausal symptoms (Menopause Rating Scale, MRS), anxiety and depression (Hospital Anxiety and Depression Scale, HAD-A and HAD-D), health-related quality of life (Nottingham Health Profile, NHP), and sleep quality (Pittsburgh Sleep Quality Index, PSQI) were collected. Correlation analyses were performed using Pearson coefficients. Logistic regression analyses were conducted to identify predictors of sleep disturbance, defined as a PSQI score ≥ 5. Results: The prevalence of sleep disturbance was 64.5%, with a median PSQI score of 6 (range, 0–19). PSQI scores were moderately correlated with MRS (r = 0.432) and NHP sleep scores (r = 0.461) (both p < 0.001), and weakly but significantly correlated with HAD-A, HAD-D, and multiple NHP subdomains including social isolation and emotional reaction (all p < 0.001). In univariate logistic regression analyses, higher total MRS, HAD-A, NHP social, emotional, sleep, and part 2 scores, as well as a history of psychiatric consultation, were significant predictors of sleep disturbance. However, in multivariate analysis, only the NHP social score remained an independent predictor (OR = 1.02, 95% CI: 1.00–1.04, p = 0.029). Conclusion: Sleep disturbance is common among breast cancer patients undergoing chemotherapy and appears to be more strongly associated with psychosocial dimensions, particularly social isolation, than with traditional biomedical variables. These findings underscore the importance of incorporating psychosocial assessments and interventions into the supportive care of this population to potentially mitigate sleep-related morbidity.