Decisions about prophylactic gynecologic surgery: a qualitative study of the experience of female Lynch syndrome mutation carriers
Bibliographic record
Abstract
BACKGROUND: Women who carry a mutation for Lynch syndrome face complex decisions regarding strategies for managing their increased cancer risks. At present, there is limited understanding of the factors influencing women's prophylactic surgery decisions. METHODS: As part of an exploratory pilot project, semi-structured interviews were conducted with 10 women who were Lynch syndrome mutation carriers and had made prophylactic surgery decisions. Nine of 10 women had chosen to undergo prophylactic hysterectomy and/or oophorectomy as a means of managing their increased gynecological cancer risks. RESULTS: Study findings revealed that surgery decisions were influenced by multiple factors, including demographic variables such as age and parity, as well as psychosocial factors such as cancer worry, in addition to personal and social knowledge of gynecological cancer. While all women were satisfied with their surgery decision, some reported they were not fully informed about the negative impact on their quality of life post-surgery (e.g., complications of surgically-induced menopause), nor about the potential for, or risks and benefits of, hormone replacement therapy. CONCLUSIONS: Study findings highlight some of the factors associated with prophylactic surgery decisions and women's perceptions about pre-surgical information provision and needs. Suggestions are made for improving the information and support provided to female carriers of a Lynch syndrome mutation.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".