Complementary Therapies as a Strategy to Reduce Stress and Stimulate Immunity of Women With Breast Cancer
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
The stress associated with cancer development leads to disturbances in the hypothalamic-pituitary-adrenal axis and suppresses important facets of the immune response. The use of complementary therapies in the treatment of women with breast cancer has demonstrated therapeutic benefits that entail improvements in the patients' quality of life. The objective of this article is to present evidence on the use of complementary therapies as a stress reduction strategy and on its stimulating effects on the immune system of women with breast cancer. This is a reflexive updating article that will support the health professionals' understanding on the use of complementary therapies in breast cancer care. The use of complementary therapies in the treatment of women with breast cancer has significantly improved these subjects' stress, depression, fatigue, anxiety, and consequently, their quality of life, as well as their immune response, which is mainly illustrated by the increased number and cytotoxic activity of natural killer cells. Clinicians, health professionals and patients need to be cautious about using complementary therapies and fully understand the real benefits and risks associated with each therapy. Little or no supporting evidence is available to clarify the effects on the immune system of women with breast cancer, and the consequent therapeutic benefits obtained through the use of these practices.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".