Systematic review of cancer-related fatigue development trajectory of breast cancer based on latent growth modeling
10.3760/cma.j.cn115682-20230427-01653
- VernacularTitle:基于潜变量增长建模的乳腺癌癌因性疲乏发展轨迹的系统评价
- Author:
Qun YU
1
;
Xueli LIU
;
Yanli YAO
;
Xinqiong ZHANG
Author Information
1. 安徽医科大学护理学院，合肥 230032
- Keywords:
Breast neoplasms;
Cancer related fatigue;
Latent growth modeling;
Trajectory;
Systematic review
- From:
Chinese Journal of Modern Nursing
2023;29(35):4843-4849
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To systematically review the development trajectory and predictors of cancer-related fatigue (CRF) in breast cancer patients.Methods:The article on CRF development trajectories of breast cancer patients using latent growth modeling research was electronically retrieved in PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, WanFang Data, VIP, and China Biomedical Literature Database. The search period was from database establishment to March 3, 2023. Two researchers conducted article screening, data extraction, and article quality evaluation, and summarized the results using descriptive analysis.Results:A total of 12 longitudinal studies were included, and 2 to 5 CRF trajectory classifications were found. Five studies described severity-based trajectories, four reported variability trends, and three delved into multidimensional patterns. Predictors of the high fatigue group were identified, including depressive symptoms, sleep disorders, anxiety, high body mass index, chronic stress, poor overall health, childhood adversity, chemotherapy, cytokines sTNF receptor-RII, IL-1 β, IL-10, and so on.Conclusions:The latent growth modeling reveals relative and similar heterogeneity trajectories of CRF, with inconsistent evidence for distinguishing different factors. It is necessary to conduct validation and in-depth research in a diverse environment, and improve the standardization of mixed model reporting, so as to provide information for early screening and the development of personalized intervention strategies.
