Acupuncture and moxibustion for chronic fatigue syndrome: A systematic review and network meta-analysis

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Abstract

Background:

Research into acupuncture and moxibustion and their application for chronic fatigue syndrome (CFS) has been growing, but the findings have been inconsistent.

Objective:

To evaluate the existing randomized clinical trials (RCTs), compare the efficacy of acupuncture, moxibustion and other traditional Chinese medicine (TCM) treatments.

Data sources:

Three English-language databases (PubMed, Embase, Web of Science, and The Cochrane Library) and 4 Chinese-language biomedical databases (Chinese Biomedical Literature Database, VIP Database for Chinese Technical Periodicals, China National Knowledge Infrastructure, and Wanfang) were searched for RCTs published from database inception through August 2021.

Study selection:

RCTs include acupuncture, moxibustion, traditional Chinese herbal medicine, western medicine and no control.

Data extraction and synthesis:

Data were screened and extracted independently using predesigned forms. The quality of RCTs was appraised with the Cochrane Collaboration risk of bias tool. We conducted a random-effects network meta-analysis within a frequentist framework. We assessed the certainty of evidence contributing to network estimates of the main outcomes with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.

Main outcomes and measures:

The primary outcomes were the overall response rate and FS-14 scale.

Results:

A total of 51 randomized controlled trials involving 3473 patients with CFS were included in this review. Forty one studies indicate low risk or unknown risk, and the GRADE scores of the combined results show low levels. Among the main indicators, traditional Chinese medicine therapies have excellent performance. However, the overall response rate is slightly different from the results obtained from the Fatigue Scale-14 total score. Moxibustion and traditional Chinese medicine (Odds ratios 48, 95% CrI 15–150) perform better in the total effective rate, while moxibustion plus acupuncture (MD 4.5, 95% CrI 3.0–5.9) is better in the FS-14 total score.

Conclusions:

The effect of acupuncture and moxibustion in the treatment of CFS was significantly higher than that of other treatments. Traditional Chinese medicine should be used more widely in the treatment of CFS.

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Most cited references 72

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Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

Xiang Wan, Wenqian Wang, Jiming Liu … (2014)

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.

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Estimating the mean and variance from the median, range, and the size of a sample

Stela Pudar Hozo, Benjamin Djulbegovic, Iztok Hozo (2005)

Background Usually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial. Methods In this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data. Results We found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n ≤ 15). For moderately sized samples (15 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy. Conclusion Using these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.

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Graphical Tools for Network Meta-Analysis in STATA

Anna Chaimani, Julian P. T. Higgins, Dimitris Mavridis … (2014)

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

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Author and article information

Contributors

Yang Fang

Han-Bo Ma

Yi-Peng Yuan

Journal

Journal ID (nlm-ta): Medicine (Baltimore)

Journal ID (iso-abbrev): Medicine (Baltimore)

Journal ID (publisher-id): MD

Title: Medicine

Publisher: Lippincott Williams & Wilkins (Hagerstown, MD )

ISSN (Print): 0025-7974

ISSN (Electronic): 1536-5964

Publication date Collection: 05 August 2022

Publication date (Electronic): 05 August 2022

Volume: 101

Issue: 31

Electronic Location Identifier: e29310

Affiliations

[a ]School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China

[b ]Shenzhen Bao’an Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong Province, China.

Author notes

*Correspondence: Bo-Wen Yue, Shenzhen Bao’an Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, 25 Yu’an Second Road, district 30, Bao’an District, Shenzhen 518102, Guangdong Province, China (e-mail: starwriter@ 123456foxmail.com ).

Article

Accession ID: 00073

DOI: 10.1097/MD.0000000000029310

PMC ID: 9351926

PubMed ID: 35945779

SO-VID: a442b238-73cc-49f1-a2c9-387ab44dd270

License:

This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 09 October 2021

Date revision received : 29 March 2022

Date accepted : 27 April 2022

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Keywords: acupuncture,chronic fatigue syndrome,moxibustion,network meta-analysis,traditional chinese medicine

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Keywords: acupuncture, chronic fatigue syndrome, moxibustion, network meta-analysis, traditional chinese medicine

Acupuncture and moxibustion for chronic fatigue syndrome: A systematic review and network meta-analysis

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Abstract

Background:

Objective:

Data sources:

Study selection:

Data extraction and synthesis:

Main outcomes and measures:

Results:

Conclusions:

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Network Medicine

Most cited references 72

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

Estimating the mean and variance from the median, range, and the size of a sample

Graphical Tools for Network Meta-Analysis in STATA

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