Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysis
Objectives: Several studies have demonstrated the positive impact of non-pharmacological Traditional Chinese Medicine (TCM) therapies on pain, fatigue, sleep quality, and quality of life in cancer survivors. However, no research has compared the effectiveness of these therapies. This study aims to c...
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| Format: | Article |
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Elsevier
2025-06-01
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| Series: | Complementary Therapies in Medicine |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0965229925000391 |
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| author | Shaowang Zhang Yuanyin Li Zhide Liang Jiaxing Dai Hong Huang Huanghui Zhang Bing Yang Jinghui Wang Dongxin Tang |
| author_facet | Shaowang Zhang Yuanyin Li Zhide Liang Jiaxing Dai Hong Huang Huanghui Zhang Bing Yang Jinghui Wang Dongxin Tang |
| author_sort | Shaowang Zhang |
| collection | DOAJ |
| description | Objectives: Several studies have demonstrated the positive impact of non-pharmacological Traditional Chinese Medicine (TCM) therapies on pain, fatigue, sleep quality, and quality of life in cancer survivors. However, no research has compared the effectiveness of these therapies. This study aims to compare various interventions and identify the most effective non-pharmacological TCM therapies to provide evidence-based recommendations for cancer survivors. Methods: A systematic search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang Data. RCTs investigating the effects of Taichi, Qigong, acupuncture, acupressure, TCM emotional therapy, and mixed therapies as interventions for cancer survivors were screened was conducted. Data from the creation of the database to February 2025 were included. Two independent reviewers evaluated the study quality. A Bayesian Network Meta-analysis was conducted to carry out a random effects model. Results: Seventy-one RCTs involving 6473 patients were included in the analysis. Network meta-analysis showed significance for all five intervention therapies in pain control in cancer patients. The best efficacy was observed for acupressure (SMD=-1.1 [-1.55, −0.66]) and Taichi/Qigong (SMD=-1.08[-1.64, −0.53]), followed by TCM emotional therapy (SMD=-0.93 [-1.42, −0.44]) and acupuncture (SMD=-0.54 [-0.93, −0.15]), with the latter showing comparatively lower efficacy. None of the interventions demonstrated superior efficacy in improving fatigue compared to the control group. Mixed therapies (SMD=-1.36[-2.56, −0.28]) demonstrated the greatest effect in improving sleep quality. Taichi/Qigong (SMD=1.87 [0.96, 2.83]) demonstrated certain advantages in improving quality of life. However, acupuncture and TCM emotional therapy had no significant effect on sleep quality or overall quality of life. Conclusion: The evidence from this study suggests that acupressure and Taichi/Qigong are recommended as the most effective therapies for pain relief and quality of life improvement, respectively. The efficacy of these therapies for fatigue remains inconclusive. However, due to the limited number of included studies and the high risk of bias, these results should be interpreted with caution. Future studies should include more rigorously designed high-quality randomized controlled trials to confirm their long-term efficacy and safety. Registration: PROSPERO CRD42024601976 |
| format | Article |
| id | doaj-art-3cda4455012044ff950d49d9bdc758a2 |
| institution | Kabale University |
| issn | 0965-2299 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Complementary Therapies in Medicine |
| spelling | doaj-art-3cda4455012044ff950d49d9bdc758a22025-08-20T03:42:29ZengElsevierComplementary Therapies in Medicine0965-22992025-06-019010316410.1016/j.ctim.2025.103164Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysisShaowang Zhang0Yuanyin Li1Zhide Liang2Jiaxing Dai3Hong Huang4Huanghui Zhang5Bing Yang6Jinghui Wang7Dongxin Tang8Guizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, ChinaGuizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, ChinaDepartment of Physical Education, College of Physical Education, Qingdao University, Qingdao 266071, ChinaGuizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, ChinaGuizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, ChinaGuizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, ChinaGuizhou University of Traditional Chinese Medicine, Guiyang 550000, China; The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, ChinaGuizhou University of Traditional Chinese Medicine, Guiyang 550000, China; The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, China; Correspondence to: Department of Oncology, the First Affiliated Hospital of Guizhou University of Chinese Medicine, Guiyang 550000, China.Guizhou University of Traditional Chinese Medicine, Guiyang 550000, China; The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550000, China; Talent Base for TCM Tumor Inheritance and Science and Technology Innovation of Guizhou Province, Guiyang 550000, China; Correspondence to: Huaxi Campus, Guizhou University of Traditional Chinese Medicine, Guiyang 550000, China.Objectives: Several studies have demonstrated the positive impact of non-pharmacological Traditional Chinese Medicine (TCM) therapies on pain, fatigue, sleep quality, and quality of life in cancer survivors. However, no research has compared the effectiveness of these therapies. This study aims to compare various interventions and identify the most effective non-pharmacological TCM therapies to provide evidence-based recommendations for cancer survivors. Methods: A systematic search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang Data. RCTs investigating the effects of Taichi, Qigong, acupuncture, acupressure, TCM emotional therapy, and mixed therapies as interventions for cancer survivors were screened was conducted. Data from the creation of the database to February 2025 were included. Two independent reviewers evaluated the study quality. A Bayesian Network Meta-analysis was conducted to carry out a random effects model. Results: Seventy-one RCTs involving 6473 patients were included in the analysis. Network meta-analysis showed significance for all five intervention therapies in pain control in cancer patients. The best efficacy was observed for acupressure (SMD=-1.1 [-1.55, −0.66]) and Taichi/Qigong (SMD=-1.08[-1.64, −0.53]), followed by TCM emotional therapy (SMD=-0.93 [-1.42, −0.44]) and acupuncture (SMD=-0.54 [-0.93, −0.15]), with the latter showing comparatively lower efficacy. None of the interventions demonstrated superior efficacy in improving fatigue compared to the control group. Mixed therapies (SMD=-1.36[-2.56, −0.28]) demonstrated the greatest effect in improving sleep quality. Taichi/Qigong (SMD=1.87 [0.96, 2.83]) demonstrated certain advantages in improving quality of life. However, acupuncture and TCM emotional therapy had no significant effect on sleep quality or overall quality of life. Conclusion: The evidence from this study suggests that acupressure and Taichi/Qigong are recommended as the most effective therapies for pain relief and quality of life improvement, respectively. The efficacy of these therapies for fatigue remains inconclusive. However, due to the limited number of included studies and the high risk of bias, these results should be interpreted with caution. Future studies should include more rigorously designed high-quality randomized controlled trials to confirm their long-term efficacy and safety. Registration: PROSPERO CRD42024601976http://www.sciencedirect.com/science/article/pii/S0965229925000391Non-pharmacological traditional Chinese medicine therapiesNetwork Meta-AnalysisCancer survivorsPainFatigue |
| spellingShingle | Shaowang Zhang Yuanyin Li Zhide Liang Jiaxing Dai Hong Huang Huanghui Zhang Bing Yang Jinghui Wang Dongxin Tang Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysis Complementary Therapies in Medicine Non-pharmacological traditional Chinese medicine therapies Network Meta-Analysis Cancer survivors Pain Fatigue |
| title | Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysis |
| title_full | Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysis |
| title_fullStr | Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysis |
| title_full_unstemmed | Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysis |
| title_short | Comparing the effects of different non-pharmacological traditional Chinese medicine therapies on cancer survivors: A Bayesian Network Meta-analysis |
| title_sort | comparing the effects of different non pharmacological traditional chinese medicine therapies on cancer survivors a bayesian network meta analysis |
| topic | Non-pharmacological traditional Chinese medicine therapies Network Meta-Analysis Cancer survivors Pain Fatigue |
| url | http://www.sciencedirect.com/science/article/pii/S0965229925000391 |
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