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Acupuncture-related therapies for drug addiction: a systematic review and network meta-analysis
HuiYan Zhao1,2, Jung-Hee Jang1,2, Yeon-Hee Ryu1,2
1KM Science Research Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea.
Introduction:
Drug addiction is a major global health problem marked by compulsive drug-seeking and profound neuropsychiatric disturbances. This systematic review and network meta-analysis aimed to evaluate the effectiveness of various acupuncture-related therapies for managing drug addiction.
Methods:
Overall, 10 databases were searched for acupuncture-related therapies for drug addiction from inception to December 20, 2025. Methodological quality was assessed using Cochrane Handbook risk of bias 2.0. Pairwise meta-analyses were performed using RevMan 5.4 software and the network meta-analyses using R software.
Results:
A total of 35 randomized controlled trials encompassing 15 intervention types with 2,812 participants were included. The most frequently targeted acupoints were PC6, ST36, and SP6, while commonly used auricular points included TF4 (Shenmen), AH6a (Jiaogan), and CO14 (lung). Network meta-analysis indicated that acupuncture therapies, particularly when integrated with usual care, significantly improved drug addiction symptoms, although efficacy varied by symptom type. Treatment duration emerged as a potential moderating factor; specifically for withdrawal symptoms, long-term interventions (>20 days) demonstrated more consistent and certain effects compared to short-term treatments. While manual acupuncture (MA) and auricular acupuncture (AA) combined with usual care showed favorable trends for depression and anxiety, respectively, these rankings should be interpreted with caution due to the limited number of studies and observed heterogeneity.
Discussion:
Overall, the findings suggest that acupuncture is a promising adjunct therapy, with treatment duration playing a critical role in achieving stable clinical outcomes in addiction management.
Systematic Review Registration:
https://www.crd.york.ac.uk/PROSPERO/recorddashboard.
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