期刊
ONCOLOGY NURSING FORUM
卷 44, 期 6, 页码 739-750出版社
ONCOLOGY NURSING SOC
DOI: 10.1188/17.ONF.739-750
关键词
breast cancer; sleep; fatigue; latent growth mixture modeling; latent class analysis; symptoms
资金
- T32 Institutional Training Grant in Cancer, Aging, and End of-Life Care [T32NR013456]
- NIH
Purpose/Objectives: To examine self-reported severity of fatigue and disturbed sleep experienced daily by women with breast cancer during multiple cycles of chemotherapy, exploring potential classes of women experiencing similar symptom trajectories. Design: In a secondary analysis, classes of women experiencing similar patterns of fatigue and disturbed sleep were identified. Setting: Oncology clinics in the United States. Sample: 166 women with breast cancer receiving chemotherapy. Methods: Severity scores were self-reported daily using an automated system. Classes of fatigue and disturbed sleep severity were identified using latent growth mixture modeling. Main Research Variables: Fatigue, disturbed sleep, age, stage of disease, education, employment, marital status, chemotherapy regimen, hours lying down, and missed work. Findings: Three fatigue classes were identified: mild decreasing (59% cycle 2, 64% cycle 3), low moderate decreasing (30% cycle 2, 25% cycle 3), and high moderate decreasing (11% both cycles). Two disturbed sleep classes were identified: mild decreasing (89% cycle 2, 81% cycle 3) and increasing (11% cycle 2, 19% cycle 3). Women in the high moderate decreasing fatigue class were more likely to have received doxorubicin (p = 0.02) and spent more hours lying down (p = 0.02). Conclusions: Patterns of symptom trajectories for fatigue and disturbed sleep were distinguished by baseline symptom severity. Implications for Nursing: Identification of women at risk for fatigue and disturbed sleep may allow clinicians to intensify symptom management.
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