Evidence map›Paper›PMID 35978992›Full record

SynthesisFrontiers in pain research (Lausanne, Switzerland)2022

Acupuncture as a Complementary Therapy for Cancer-Induced Bone Pain: A Systematic Review and Meta-Analysis.

Zhaobo Yan, Zhimiao MuRong, Bixiu Huo, Huan Zhong, Chun Yi, Mailan Liu, Mi Liu

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in pain research (Lausanne, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Acupuncture in cancer care: recommendations for safe practice (peer-reviewed expert opinion).Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Zhaobo YanCollege of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Hunan, China.
Zhimiao MuRongCollege of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Hunan, China.
Bixiu HuoHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Huan ZhongCollege of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Hunan, China.
Chun YiDepartment of Pathology, Hunan University of Chinese Medicine, Hunan, China.
Mailan LiuCollege of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Hunan, China.
Mi LiuCollege of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Hunan, China.
Hunan University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cancer-induced bone pain (CIBP) is a special type of cancer pain and lacks safe and effective treatments. Acupuncture is a potentially valuable treatment for CIBP, studies evaluating the effect of acupuncture on CIBP have increased significantly, but the safety and efficacy of acupuncture to control CIBP remains controversial. Objective: To provide the first meta-analysis to evaluate the safety and efficacy of acupuncture in CIBP management. Data Sources: CNKI, CBM, Wanfang, VIP Database, PubMed, Embase, and Cochrane Library were searched from their inception until 1 June 2022. Study Selection: RCTs with primary bone tumor patients or other types of primary cancer companied by bone metastases as the research subjects and to evaluate the efficacy of acupuncture treatment alone or combined with the control treatment were included. Meanwhile, RCTs should choose the pain score as the primary outcome and pain relief rate, frequency of breakthrough pain, analgesic onset time, analgesia duration, quality of life, and adverse events as reference outcomes. Data Collection and Analysis: We designed a data-extraction form that was used to extract key information from the articles. Data extraction study evaluation was conducted independently by two reviewers, and a third reviewer would resolve any disagreements. The risk of bias was assessed by the Cochrane Collaboration's tool for assessing the risk bias. The quality of the evidence for main outcomes was evaluated by the GRADE system. Mean differences (MD), relative risk (RR), and 95% confidence intervals (CIs) were calculated. The forest plots were performed using the Review Manager Software (5.3 version). Subgroup analysis was used to investigate the possible sources of potential heterogeneity. Descriptive analysis was performed in case of unacceptable clinical heterogeneity. Results: Thirteen RCTs (with 1,069 patients) were included, and all studies were at high risk of bias owing to lack of blinding or other bias. Eleven studies evaluated the effectiveness of acupuncture as a complementary therapy, and showed that acupuncture plus control treatment (compared with control treatment) was connected with reduced pain intensity (MD = -1.34, 95% CI -1.74 to -0.94; Q < 0.1; Conclusion: Acupuncture has a certain effect as a complementary therapy on pain management of CIBP, which not only mitigates the pain intensity but also improves the quality of life and reduces the incidence of opioids' side effects, although the evidence level was very low. In future, a larger sample size and rigorously designed RCTs are needed to provide sufficient evidence to identify the efficacy and safety of acupuncture as a treatment for CIBP.

Indexed as

acupuncturea systematic reviewcancer-induced bone paincancer painmeta-analysis

Identifiers

PMID35978992
PMCPMC9377524
OpenAlexW4289130383

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.