Acupuncture therapies for cancer-related fatigue: A Bayesian network meta-analysis and systematic review

Front Oncol. 2023 Mar 27:13:1071326. doi: 10.3389/fonc.2023.1071326. eCollection 2023.

Abstract

Background: Cancer-related fatigue (CRF) is one of the most commonly reported symptoms impacting cancer survivors. This study evaluated and compared the effectiveness and safety of acupuncture treatments for CRF.

Methods: We searched PubMed, Embase, Web of Science, Cochrane Library, China Biology Medicine China National Knowledge Infrastructure, China Science and Technology Journal Database, and WanFang Database from inception to November 2022 to identify eligible randomized controlled trials (RCTs) comparing acupuncture treatments with sham interventions, waitlist (WL), or usual care (UC) for CRF treatment. The outcomes included the Cancer Fatigue Scale (CFS) and Pittsburgh Sleep Quality Index (PSQI), and pair-wise and Bayesian network meta-analyses were performed using STATA v17.0.

Results: In total, 34 randomized controlled trials featuring 2632 participants were included. In the network meta-analysis, the primary analysis using CFS illustrated that point application (PA) + UC (standardized mean difference [SMD] = -1.33, 95% CI = -2.02, -0.63) had the highest probability of improving CFS, followed by manual acupuncture (MA) + PA (SMD = -1.21, 95% CI = -2.05, -0.38) and MA + UC (SMD = -0.80, 95% CI = -1.50, -0.09). Moreover, the adverse events of these interventions were acceptable.

Conclusion: This study demonstrated that acupuncture was effective and safe on CRF treatment. However, further studies are still warranted by incorporating more large-scale and high-quality RCTs.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42022339769.

Keywords: acupuncture; acupuncture therapy; cancer-related fatigue; network meta-analysis; systematic review.

Publication types

  • Systematic Review

Grants and funding

This research was supported by a grant from Key Research Program of Science and Technology Department of Sichuan Province (Nos. 2021YFS0087 and 2021ZYD0103).