Evidence map›Paper›PMID 37551854›Full record

ReviewIntegrative cancer therapies

Research on Electroacupuncture Parameters for Cancer Pain Based on Data Mining.

Quan-Yao Li, Wen-Xiao Yang, Hui Liu, Li-Jing Jiao, Ya-Bin Gong, Jun Shi

Open access · goldAbstract readReview
In one paragraph

Review in Integrative cancer therapies. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Progress in pain mechanisms and management.Signal transduction and targeted therapy · 2026
    Review
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  6. Article
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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

6 authors at 1 institution in 1 country.

Quan-Yao LiDepartment of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID 0000-0002-1496-9221
Wen-Xiao YangDepartment of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Hui LiuDepartment of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID 0000-0002-9863-3345
Li-Jing JiaoDepartment of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Ya-Bin GongDepartment of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Jun ShiDepartment of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Shanghai University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer pain, a common complication of this disease, has been widely treated by electroacupuncture in recent years. However, there are numerous treatment parameters that are not conducive to clinical translation applications. This study aims to summarize the stimulation parameters commonly used in electroacupuncture treating cancer pain by data mining and visualization techniques to provide a basis for the future acupuncture technology transformation and selection of optimal stimulation parameters.

methodsNine databases, including Pubmed, Cochrane Library, Embase, Web of Science, OVID, China National Knowledge Infrastructure Database, China Biology Medicine disk, China Science and Technology Journal Database, and Wanfang Database, were searched for clinical studies on electroacupuncture treatment cancer pain published between January 2012 and September 2022. A database was established using Microsoft Excel 2020 and analyzed with SPSS Modeler 18.1 software and SPSS statistics 26.0 software.

resultsTwenty-four articles were included according to the established criteria. The most used electroacupuncture stimulation parameters were a dilatational wave, the current frequency of 2/100 Hz, stimulation duration of 30 minutes per treatment, and frequency of treatment once a day. Fifty-eight acupoints were mentioned, and the total frequency of acupoints involved was 156 times. The most used ones include Zusanli (ST36), Sanyinjiao (SP06), Hegu (LI04), Neiguan (PC06), Quchi (LI11), Taichong (LR03), Ashi point, Jiaji point, and those most generally used acupoints that are closely arranged on the Stomach Channel of Foot Yangming and the Spleen Channel of Foot Taiyin. The association analysis of acupoints revealed that the most supported acupoint pair was Sanyinjiao (SP06) and Zusanli (ST36). Cluster analysis demonstrated 3 groups, 1 for obligatory acupoints, 1 for Ashi point, and the third for Jiaji point.

conclusionsA dilatational wave, the current frequency of 2/100 Hz, 30-minute stimulation, and acupoints of the Stomach Channel of Foot Yangming and the Spleen Channel of Foot Taiyin selection are frequently used in electroacupuncture for treating cancer pain. Due to the limitations of this study, further research and more standardized, multi-center, large-sample clinical trials can be carried out to guide optimizing acupuncture treatment schemes and promote the formation of TCM-characteristic technologies for cancer pain.

Indexed as

Acupuncture TherapyCancer PainElectroacupunctureMeridiansNeoplasmsData MiningHumanscancer paindata miningelectroacupunctureparametertraditional Chinese medicine

Identifiers

PMID37551854
PMCPMC10411286
OpenAlexW4385671889

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.