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Record W4412924099 · doi:10.3389/fphar.2025.1639714

Effects of the efficacy of the Yi Shen Tiao Gan formula on aromatase inhibitor associated musculoskeletal syndrome: a randomized controlled trial

2025· article· en· W4412924099 on OpenAlexaboutno aff
Yan Zhang, Meiling Chu, Meina Ye, Yiqin Cheng, Hui Cong, Yulian Yin, Hongfeng Chen

Bibliographic record

VenueFrontiers in Pharmacology · 2025
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsnot available
FundersShanghai University of Traditional Chinese Medicine
KeywordsMedicineDiscontinuationWOMACRandomized controlled trialInternal medicineAromatase inhibitorOsteoarthritisBone remodelingBreast cancerAromataseAlternative medicineCancer

Abstract

fetched live from OpenAlex

Background: Aromatase inhibitor-induced musculoskeletal syndrome (AIMSS) has emerged as a major cause of treatment discontinuation in hormone receptor-positive patients treated with aromatase inhibitors. There are currently no standardized guidelines or universally accepted treatments for AIMSS. Therefore, this exploratory study aimed to preliminarily evaluate the efficacy and safety of Yi Shen Tiao Gan formula in AIMSS patients. Methods: A total of 136 patients with AIMSS were included in this single-center, randomized, controlled, single-blind trial and were randomised into the treatment and control groups at a ratio of 1:1. All patients were routinely given Caltrate D. Patients in the treatment group took Breast surgery formula combined with Yi Shen Tiao Gan formula and control group took Breast surgery formula twice a day. The treatment period of Chinese medicine was 3 months as one course of treatment. The clinical efficacy of two courses of treatment was observed in this study. The study observed and compared the following indicators between the two groups: the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, Traditional Chinese Medicine symptom and sign scores, bone mineral density, bone metabolism biochemical indicators, bone metabolism-related hormones and safety assessments. Results: > 0.05), but the decrease in β-CTX was slightly slower in the treatment group of the AI + OFS population compared to the control group. After applying Bonferroni correction for multiple testing, these associations did not reach statistical significance. No serious adverse events were observed in either group. Conclusion: The YSTG formula significantly reduced WOMAC scores, improving pain, stiffness, physical function in patients with AIMSS, and alleviating the traditional Chinese medicine symptoms and signs of liver and kidney deficiency, thereby enhancing the overall quality of life for patients. Clinical Trial Registration: http://www.chictr.org.cn, identifer ChiCTR2200057785.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.317
Teacher spread0.312 · 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 designRandomized trial
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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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