Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Mar 21:12:100692.
doi: 10.1016/j.apjon.2025.100692. eCollection 2025 Dec.

The interplay between sleep and cancer-related fatigue in breast cancer: A casual and computer-simulated network analysis

Hongman Li  1 , Ying Xiong  1 , Qihan Zhang  2 , Yufei Lu  1 , Qiaoling Chen  1 , Siqi Wu  2 , Yiguo Deng  2 , Chunmin Yang  3 , M Tish Knobf  4 , Zengjie Ye  2
Affiliations

The interplay between sleep and cancer-related fatigue in breast cancer: A casual and computer-simulated network analysis

Hongman Li et al. Asia Pac J Oncol Nurs. .

Abstract

Objective: Sleep problems and cancer-related fatigue are common symptoms in women for breast cancer, during and after treatment. Identifying key intervention targets for this symptom cluster may improve patient reported outcomes. This study aimed to explore the relationship between sleep and cancer-related fatigue to identify optimal intervention targets.

Methods: In the "Be Resilient to Breast Cancer" program, self report data were collected on sleep and cancer-related fatigue the Multidimensional Fatigue Symptom Inventory-Short Form and the Pittsburgh Sleep Quality Index. Gaussian network analysis was employed to identify central symptoms and nodes, while a Bayesian network explored their causal relationships. Computer-simulated interventions were used to identify core symptoms as targets for intervention.

Results: General fatigue (Str ​= ​0.95, Bet ​= ​7, Clo ​= ​0.007) was considered the node with the strongest centrality. The daytime dysfunction item on the Pittsburgh sleep quality index had the strongest bridge strength. Core symptoms were identified as targets for intervention by the computer-simulated analysis.

Conclusions: Sleep quality is the strongest predictor of cancer-related fatigue from a casual networking perspective. Sleep latency and daytime dysfunction should be targeted to break the chained symptom interaction between sleep and cancer-related fatigue.

Keywords: Breast neoplasms; Fatigue; Network analysis; Sleep quality.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest. The corresponding author, Prof. Zengjie Ye, is an editorial board member of Asia–Pacific Journal of Oncology Nursing. The article was subject to the journal's standard procedures, with peer review handled independently of Prof. Ye and their research groups.

Figures

Fig. 1
Fig. 1
Gaussian network analysis visualization and centrality metrics for sleep and CRF. (A) The depict of Gaussian network structures. (B) Centrality metrics of core symptoms. (C) Centrality metrics of bridge symptoms. CRF, Cancer-related fatigue.
Fig. 2
Fig. 2
The depict of the Bayesian network model of symptoms. CRF, Cancer-related fatigue.
Fig. 3
Fig. 3
The effect of computer-simulated interventions on the symptoms. (A) Projected Effects of alleviating intervention depicted by sum score of target symptoms. (B) Projected Effects of aggravating intervention depicted by sum score of target symptoms.
See this image and copyright information in PMC

References

    1. Connolly J.L., Boyages J., Schnitt S.J., et al. In situ carcinoma of the breast. Annu Rev Med. 1989;40:173–180. doi: 10.1146/annurev.me.40.020189.001133. - DOI - PubMed
    1. Ruiz-Casado A., Álvarez-Bustos A., de Pedro C.G., Méndez-Otero M., Romero-Elías M. Cancer-related fatigue in breast cancer survivors: a review. Clin Breast Cancer. Feb 2021;21(1):10–25. doi: 10.1016/j.clbc.2020.07.011. - DOI - PubMed
    1. Li Y., Yuan C. Levels of fatigue in Chinese women with breast cancer and its correlates: a cross-sectional questionnaire survey. J Am Acad Nurse Pract. Mar 2011;23(3):153–160. doi: 10.1111/j.1745-7599.2010.00591.x. - DOI - PubMed
    1. Abrahams H.J.G., Gielissen M.F.M., Verhagen C., Knoop H. The relationship of fatigue in breast cancer survivors with quality of life and factors to address in psychological interventions: a systematic review. Clin Psychol Rev. Jul 2018;63:1–11. doi: 10.1016/j.cpr.2018.05.004. - DOI - PubMed
    1. Berger A.M., Mooney K., Alvarez-Perez A., et al. Cancer-related fatigue, version 2.2015. J Natl Compr Cancer Netw. Aug 2015;13(8):1012–1039. doi: 10.6004/jnccn.2015.0122. - DOI - PMC - PubMed

LinkOut - more resources