Incidence, Management, and Prevention of Gynecomastia and Breast Pain in Patients with Prostate Cancer Undergoing Antiandrogen Therapy: A Systematic Review and Meta-analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Background and objective: In patients with prostate cancer treated with antiandrogen monotherapy, gynecomastia and breast pain are relatively common. In the setting of androgen receptor pathway inhibitors (ARPIs), the incidence of these adverse events (AEs) remains unclear. In addition, the effect of prophylactic treatment on gynecomastia remains uncertain. We aimed to evaluate the incidence of gynecomastia and breast pain in prostate cancer patients treated with ARPIs compared with androgen deprivation therapy (ADT) and the effect of prophylactic treatment for these AEs due to antiandrogen therapy. Methods: In June 2024, we queried four databases-PubMed, Scopus, Web of Science, and Embase-for randomized controlled trials (RCTs) investigating prostate cancer treatments involving antiandrogen therapy. The endpoints of interest were the incidence of these AEs due to ARPIs and the effect of prophylactic treatment for these. Key findings and limitations: = 0.2). Prophylactic tamoxifen or radiotherapy reduced significantly the incidence of gynecomastia and breast pain caused by bicalutamide monotherapy. Conclusions and clinical implications: We found that ARPI monotherapy increases the incidence of these AEs significantly compared with ADT. In contrast, ARPI plus ADT therapy did not result in a higher incidence of AEs. The use of either tamoxifen or radiotherapy was effective in reducing the incidence of these AEs due to bicalutamide monotherapy. These prophylactic treatments could reduce the incidence of AEs due to ARPI monotherapy. However, further studies are needed to clarify their efficacy. Patient summary: Although androgen deprivation therapy (ADT) improves overall survival in patients with prostate cancer, it is associated with several complications. Androgen receptor pathway inhibitor (ARPI) monotherapy has emerged as a promising strategy for improving oncological outcomes in these patients. However, ARPI monotherapy increases gynecomastia and breast pain in prostate cancer patients compared with ADT, while ARPI plus ADT did not result in a higher incidence of adverse events.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".