Effectiveness of Pelvic Floor Muscle and Education-based Therapies on Bladder, Bowel, Vaginal, Sexual, Psychological Function, Quality of Life, and Pelvic Floor Muscle Function in Females Treated for Breast Cancer: A Systematic Review
Bibliographic record
Abstract
PURPOSE OF REVIEW: Breast malignancy is the most common cancer in females. Symptoms of pelvic floor disorders and sexual dysfunction secondary to systemic cancer treatment may occur. Non-surgical, non-pharmaceutical conservative therapies, namely pelvic floor muscle (PFM) and education-based therapies, could be beneficial to reduce these symptoms in this population. This systematic review aimed to examine the evidence regarding their effectiveness on bladder, bowel, vaginal, sexual, psychological function, quality of life, and PFM function in breast cancer populations. RECENT FINDINGS: Six databases were searched to identify interventional studies on the effect of PFM therapies, education-based therapies, or combined (multimodal) therapies on any outcome of interest. The search yielded 603 results, from which 12 studies were included. Of these, six (50%) were RCTs, one (8%) was a non-RCT with two groups, and five (42%) were non-RCTs with a single group. Findings suggest that PFM therapies (active) may be beneficial, and education in the format of CBT may improve bladder function. No data were found for bowel function and results from two RCTs were inconclusive to draw conclusions for vaginal function. Sexual function was the most frequently reported outcome. PFM therapies (active > passive) may be beneficial, and education is more likely than not to improve sexual function. For psychological function, PFM therapies (active + passive) may be beneficial, and education is more unlikely than likely to improve psychological function. For quality of life, PFM therapies (active + passive) may be beneficial, and education is more unlikely than likely to improve quality of life, although CBT combined with physical exercise may provide further improvement. PFM therapies (active ± passive) may improve PFM function. Given the limited number of studies and their methodological limitations, caution should be exercised when interpreting these study results. More research is needed to confirm findings and to investigate the clinical value of PFM therapies and combined, multimodal therapies for breast cancer populations. Non-surgical, non-pharmaceutical conservative therapies may be helpful for breast cancer populations. Clinicians should consider the highest level of available evidence to guide their practice and use their clinical judgement to select the treatment components and appropriate dosages.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".