Prophylactic Mastectomy: Indications, Options, and Reconstructive Alternatives
Bibliographic record
Abstract
Prophylactic mastectomy continues to be a controversial procedure as a preventive tool against breast cancer. Recent research and other scientific advances, however, have refocused attention on better risk estimation, evidence of efficacy, and improvements in reconstruction. The recently discovered genetic markers BRCA1 and BRCA2 have become increasingly important in determining risk; a BRCA1-positive patient's risk of developing breast cancer by the age of 65 is estimated at 50 percent to 80 percent. BRCA1- and BRCA2-positive breast cancers also tend to be higher grade and occur in younger women (making mammography less effective). Genetically linked breast cancers are usually estrogen receptor negative, making them less susceptible to chemoprevention. Various predictive models and recommendations by experts in the field are also available for today's clinicians to ascertain who should be genetically tested. The benefit of bilateral prophylactic mastectomy, although difficult to estimate, can be evaluated by looking at the incidence of breast cancer in studies of patients who have previously undergone prophylactic mastectomy. The estimated risk reduction from these studies is 80 percent to 95 percent. Similarly, life expectancy is believed to be increased from 2.9 to 5.3 years. The psychological benefits include a 70 percent rate of satisfaction and a decrease in emotional concern over developing breast cancer by 74 percent of women who underwent prophylactic mastectomy. Although reconstruction results may vary, most patients have been very satisfied and some may achieve cosmetic results that are better than their preoperative situation. Patient selection for specific types of reconstruction after prophylactic mastectomy and the decision to proceed should be based on surgical risk and the likelihood of a good outcome. The choice of mastectomy incision should consider the size of the breast, preexisting scars, patient risk factors, and the planned method and goal of reconstruction. The authors propose certain guidelines based on degree of ptosis and cup size when planning prophylactic mastectomies with reconstruction. In certain cases, a nipple-sparing mastectomy may provide cosmetic advantages that could outweigh the additional oncologic risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".