Acupuncture for cancer pain: an evidence-based clinical practice guideline.

Abstract

BACKGROUND:

This study aims to develop an evidence-based clinical practice guideline of acupuncture in the treatment of patients with moderate and severe cancer pain.

METHODS:

The development of this guideline was triggered by a systematic review published in JAMA Oncology in 2020. We searched databases and websites for evidence on patient preferences and values, and other resources of using acupuncture for treatment of cancer pain. Recommendations were developed through a Delphi consensus of an international multidisciplinary panel including 13 western medicine oncologists, Chinese medicine/acupuncture clinical practitioners, and two patient representatives. The certainty of evidence, patient preferences and values, resources, and other factors were fully considered in formulating the recommendations. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was employed to rate the certainty of evidence and the strength of recommendations.

RESULTS:

The guideline proposed three recommendations: (1) a strong recommendation for the treatment of acupuncture rather than no treatment to relieve pain in patients with moderate to severe cancer pain; (2) a weak recommendation for the combination treatments with acupuncture/acupressure to reduce pain intensity, decrease the opioid dose, and alleviate opioid-related side effects in moderate to severe cancer pain patients who are using analgesics; and (3) a strong recommendation for acupuncture in breast cancer patients to relieve their aromatase inhibitor-induced arthralgia.

CONCLUSION:

This proposed guideline provides recommendations for the management of patients with cancer pain. The small sample sizes of evidence limit the strength of the recommendations and highlights the need for additional research.

• Authors: Long Ge, Qi Wang, Yihan He, Darong Wu, Qi Zhou, Nenggui Xu, Kehu Yang, Yaolong Chen, Anthony Lin Zhang, Haiqing Hua, Jinchang Huang, Ka-Kit Hui, Fanrong Liang, Linpeng Wang, Bin Xu, Yufei Yang, Weimin Zhang, Baixiao Zhao, Bing Zhu, Xinfeng Guo, Charlie Changli Xue, Haibo Zhang, International Trustworthy traditional Chinese Medicine Recommendations (TCM Recs) Working Group
• Journal: Chinese medicine (Chin Med) Vol. 17 Issue 1 Pg. 8 (Jan 05 2022) ISSN: 1749-8546 [Print] England
• PMID: 34983587 (Publication Type: Journal Article, Review)
• Copyright: © 2022. The Author(s).