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Preliminary effectiveness and acceptability of single-session acupuncture with infusion therapy at an academic cancer center.

2025· article· en· W4410803264 on OpenAlexaboutno aff
Jacob Hill, Laura Shoemaker, Thuy Nguyen, Robert Saper

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcupunctureSession (web analytics)Center (category theory)CancerPhysical therapyCancer therapyFamily medicineMedical physicsAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

e24048 Background: Acupuncture is an evidence-based integrative oncology treatment gaining popularity among cancer patients and providers for addressing cancer-related side effects. Acupuncture is included in several ASCO integrative oncology guidelines, including for pain management 1,2 , anxiety and depression 2,3 , stress 2 , chemotherapy-induced nausea and vomiting 2 , fatigue 2,4 , hot flashes 2 , and quality of life. 2 Most acupuncture research focuses on 6-8 week interventions, with less known regarding short-duration, single-session, interventions. This study explores the preliminary effectiveness and acceptability of a single acupuncture treatment administered concurrently with infusion therapy. Methods: We conducted a quality assessment/quality improvement (QA/QI) study of acupuncture for adults receiving infusion therapy at the Cleveland Clinic Taussig Cancer Center from October 1 – December 31, 2024. Patients received a single 20-minute acupuncture session during infusion therapy to address current symptoms and/or improve quality of life. Questionnaires were completed pre/post treatment to assess satisfaction (acceptability), familiarity and prior use of acupuncture, and current symptoms (Edmonton Symptom Assessment Survey (ESAS)). Descriptive statistics were used to summarize demographics and QA/QI outcomes. T-tests of mean differences were used to calculate p-values for the pre/post symptom change. Results: A total of 93 acupuncture treatments were administered. Most patients were female (61.2%), White (81.3%) with an average age of 59.6 years old (SD 11.6). Common diagnoses included breast cancer (18.7%), lymphoma (17.3%) and multiple myeloma (17.3%). Most patients never received acupuncture before (53%), were only somewhat familiar with acupuncture (31%), and 84% reported being very satisfied with treatment. We found significant (p<0.001) pre/post reductions in anxiety, depression, drowsiness, loss of appetite, nausea, pain, shortness of breath, tiredness, and a significant increase in wellbeing (Table). No significant adverse events were reported. Conclusions: This study supports the preliminary effectiveness and acceptability of short duration, single session, acupuncture concurrently with infusion therapy. Symptom change pre/post infusion suite acupuncture. Symptom t df p-value (2-tailed) Mean Difference 95% CI (Lower) 95% CI (Upper) Anxiety 8.53 92 <0.001 1.86 1.43 2.29 Depression 5.67 92 <0.001 1.06 0.69 1.44 Drowsiness 5.86 92 <0.001 1.45 0.96 1.94 Loss of Appetite 6.69 92 <0.001 1.27 0.89 1.65 Nausea 4.02 92 <0.001 0.75 0.38 1.12 Pain 5.32 92 <0.001 1.11 0.69 1.52 Shortness of Breath 5.69 92 <0.001 1.13 0.74 1.52 Tiredness 9.19 92 <0.001 2.02 1.58 2.46 Wellbeing 5.23 92 <0.001 1.28 0.79 1.76 T-tests of mean differences were used to calculate p-values, df = degrees of freedom, CI = confidence interval.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.115
GPT teacher head0.529
Teacher spread0.414 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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