Background:
Cancer-related fatigue (CRF) is one of the most common adverse events of anticancer therapies, with an incidence of up to 90%, which seriously affects the quality of life in cancer patients. Complementary and alternative therapies for CRF include acupuncture, Chinese herbal medicine, Tai Chi, Qigong, and massage therapy. Several studies have shown that traditional Chinese medicine (TCM) exercise therapies, such as Tai Chi, Ba Duan Jin, the classics of tendon changing, Six Healing Sounds, and Wu Qin Xi, can improve CRF, anxiety symptoms, and sleep quality in cancer patients. However, their specific efficacy and which TCM exercise therapy is the best remain controversial. In this study, we assess and compare the effects of different TCM exercise therapies on CRF, anxiety, and sleep quality in cancer patients by network meta-analysis (NMA).
Methods:
Randomized controlled trials reporting TCM exercise therapies for CRF, anxiety and sleep quality in cancer patients published before October 2021 will be searched in the PubMed, Web of Science, Scopus, Cochrane Library, Embase, China Scientific Journal Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, and Wanfang Data. Two researchers will be independently responsible for literature screening, data extraction and assessment of their quality. Standard pair-wise and NMA will be performed to compare the efficacy of different TCM exercise therapies on CRF, anxiety and sleep quality in cancer patients using Stata 14.0 software.
Results:
The results of this meta-analysis will be submitted to a peer-reviewed journal for publication.
Conclusions:
This NMA will contribute to identify the optimal TCM exercise therapy for CRF and provide evidence-based bias for clinical decision-making.
Ethics and dissemination:
Ethical approval was not required for this study. The systematic review will be published in a peer-reviewed journal, presented at conferences, and shared on social media platforms.
Osf registration number:
DOI 10.17605/OSF.IO/MJ8DA.
PMID: 34871250 DOI: 10.1097/MD.0000000000027681
