The maintenance effect of acupuncture on the side effects of breast cancer endocrine therapy
Bibliographic record
Abstract
BACKGROUND: Breast cancer is common among women throughout the world and endocrine therapy is an established part of its treatment. But, unfortunately, this has also resulted in intolerable side effects affecting the quality of life. Acupuncture has been widely used to treat endocrine-related side effects in patients with breast cancer, but how long its effect can be maintained has not been published. The systematic review is designed to evaluate the maintenance efficacy of acupuncture for related side effects after breast cancer endocrine therapy. METHODS AND ANALYSIS: We will search for the following databases: PubMed, Embase, Cochrane Library, Web of Science, including China National Knowledge Infrastructure (CNKI), WanFang Data, Technology Periodical Database (VIP), and China Biology Medicine (CBM) from inception to May 2020. Two reviewers will search these databases, collect all articles, and assess the quality of studies separately, and there will be no limitations on language. The primary outcomes will be assessed using acupuncture for endocrine-related hot flashes and joint pain duration (1 month, 3 months, 6 months). Measurement tools include the Kupperman index, Brief Pain Inventory Short Form (BPI-SF), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Brief Pain Inventory-Short (BPI-SF). We will use RevMan V.5.3 for meta-analysis and employ the Grading of Recommendations Assessment, Development and Evaluation System to assess the quality of evidence. RESULTS: This systematic review will evaluate the maintenance efficacy of acupuncture on the side effects of breast cancer endocrine therapy. CONCLUSION: This study will provide high-quality current evidence of how long its effect can be maintained after acupuncture for related side effects after breast cancer endocrine therapy. ETHICS AND DISSEMINATION: Ethical committee approval is not required for this systematic review as patient data will not be collected. This study will help to inform doctors and researchers on the duration of acupuncture treatment for endocrine-related hot flashes and joint pain. The results will be published in a peer-reviewed journal and will be disseminated in relevant conferences. INPLASY REGISTRATION NUMBER: INPLASY202040024.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".