Evidence map›Paper›PMID 40072712›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2025

The impact of combined Gua Sha and myofascial release techniques on upper limb dysfunction in patients with breast cancer and axillary web syndrome: a prospective case series study.

Ruping Sun, Yanyan Liao

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Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07576270 (Combined Effect of Resisted Deep Breathing and Myofascial Release on Pain, Respiratory Efficiency, Chest Mobility and Lymph Edema in Postmastectomy), which is not on this map. Not yet cited in PubMed.

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1 · What the graph read from it

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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.

NCT07576270 narecruitingnot on this map

Combined Effect of Resisted Deep Breathing and Myofascial Release on Pain, Respiratory Efficiency, Chest Mobility and Lymph Edema in Postmastectomy

TypeinterventionalSponsorRiphah International UniversityRan2025 to 2026Enrolled48ConditionsPost Mastectomy LymphedemaArmsResisted Deep Breathing, Myofascial release
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Ruping SunDepartment of Breast Surgery, Jiangsu Province Hospital, No. 368 Jiangdong North Road, Gulou District, Nanjing City, 210000, Jiangsu Province, China.
Yanyan LiaoDepartment of Breast Surgery, Jiangsu Province Hospital, No. 368 Jiangdong North Road, Gulou District, Nanjing City, 210000, Jiangsu Province, China. liaoyanyan_2024@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the effects of a combined Gua Sha and myofascial release approach on upper limb dysfunction in patients with breast cancer and axillary web syndrome (AWS).

methodsIn this prospective case series study, 30 patients with breast cancer diagnosed with AWS post-surgery were recruited. Participants underwent a 12-week intervention combining Gua Sha and myofascial release techniques. Upper limb function (primary outcome) was assessed using the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire. Secondary outcomes included pain intensity (Visual Analog Scale [VAS]), range of motion (goniometry) and quality of life. Assessments were conducted at baseline, 6 weeks and 12 weeks.

resultsSignificant improvements were observed in upper limb function, with mean DASH scores decreasing from 52.3 ± 15.7 at baseline to 28.6 ± 12.4 at 12 weeks (p < 0.001). Pain intensity showed a marked reduction, with mean VAS scores decreasing from 6.8 ± 1.5 to 3.2 ± 1.8 (p < 0.001). Range of motion improved across all measured joints, with shoulder abduction showing the most substantial gain (mean increase: 35.2° ± 12.8°, p < 0.001). Quality of life scores also demonstrated significant enhancement, particularly in physical functioning and pain domains.

conclusionThe combined approach of Gua Sha and myofascial release techniques shows promising results in improving upper limb function, reducing pain and enhancing the quality of life in patients with breast cancer and AWS. These findings warrant further investigation through randomised controlled trials to establish the efficacy of this intervention compared with standard care.

Indexed as

Breast NeoplasmsFasciotomyUpper ExtremityAdultAgedAxillaFemaleHumansMiddle AgedPain MeasurementProspective StudiesQuality of LifeRange of Motion, ArticularSurveys and QuestionnairesSyndromeAxillary web syndromeBreast cancerGua ShaMyofascial limb function releaseRehabilitationUpper

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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.