The Impact of Radiation Therapy on Sexual Health in Breast, Cervix, and Prostate Cancer Patients: A Systematic Review
Bibliographic record
Abstract
Purpose: To examine the effects of radiation therapy on sexual health in cervical, breast, and prostate cancer patients. Methods: Four electronic databases (PubMed/PubMed Central, Google Scholar, Embase(Ovid), and SCOPUS) were searched, and articles published in English from January 1, 2011, through 2022 were extracted. Five reviewers independently selected primary studies that reported patient sexual health symptoms caused by cervical, breast, or prostate cancer following radiation therapy treatment. The primary outcome measures sexual health trends during or after radiation therapy through external beam radiotherapy or brachytherapy where applicable. Secondary outcomes measured predictive factors contributing to sexual health scores (age, race, and geographical location). Results: 32 studies with a total of 5033 individuals were included in the systematic review. Overall, 19 studies reported a reduction in sexual health trends, 8 reported mixed trends, and 4 reported no significant trends in sexual health. Of the 10 breast cancer studies, 6 reported decreased sexual well-being, 2 found no trends, and 2 stated mixed trends. Among 12 prostate cancer studies, 5 reported worsening sexual health, 2 found no trends, 1 reported positive sexual functioning, and 4 found mixed trends. Among 10 cervical cancer studies, 8 reported worse sexual health, while 2 reported mixed trends. Younger breast and cervical cancer patients who received radiation therapy experienced greater body image and sexual health concerns. Evidence was insufficient to evaluate trends in geographical location or race between sexual health and radiation therapy. Conclusion: In this study, prostate, breast, and cervical cancer patients who received radiation therapy treatment experienced more troublesome sexual health symptoms compared to non-irradiated cancer patients. Interventions to improve sexual health should be prioritized.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".