Longitudinal Analysis of Sleep Disturbance in Breast Cancer Survivors.

BACKGROUND: Breast cancer survivors (BCS) often report poor sleep quality and wakefulness throughout the night as the greatest challenges experienced during and posttreatment.

OBJECTIVES: This study aimed to elucidate characteristics of sleep disturbances and determine potential predictors that affect sleep disturbances in BCS for 2 years postchemotherapy.

METHODS: This is a secondary analysis of data from the EPIGEN study, which longitudinally examined sociodemographic and cancer-related factors, lifestyle, symptom characteristics, and epigenetic factors at baseline prior to chemotherapy (T1), the midpoint (T2), 6-month (T3), 1-year (T4), and 2-year (T5) time points postchemotherapy. Temporal lifestyle changes, symptom characteristics, and epigenetic factors were explored using linear mixed-effects models with a random intercept. A linear regression model was fitted to identify significant predictors of sleep disturbances at each time point.

RESULTS: In 74 BCS with an average age of 51 years and 70% non-Hispanic White, BCS experienced severe sleep disturbances at T2, which gradually improved over time. Significant temporal changes in midsleep awakenings, early awakenings, and fatigue at work were observed, with disturbances being elevated at T2. Anxiety (T1, T2, and T4), fatigue (T3 and T4), and perceived stress (T3) were significant predictors after adjusting for radiation therapy, surgery, and adjuvant endocrine therapy.

DISCUSSION: This study highlights that predictors of sleep disturbances change over time, with anxiety being a factor earlier in the treatment trajectory (prechemotherapy) and continuing over time with fatigue and perceived stress being involved later in the treatment trajectory. Our results indicate that symptom management strategies to address sleep disturbances should be tailored to the temporal factors that may change in severity during active treatment and early survivorship period. Findings gained from this study on sleep disturbance patterns and the potential risk factors can be incorporated into clinical practice in planning education and developing interventions.