Opportunistic salpingectomy for ovarian cancer prevention
Bibliographic record
Abstract
Recently accumulated evidence has strongly indicated that the fallopian tube is the site of origin for the majority of high-grade serous ovarian or peritoneal carcinomas. As a result, recommendations have been made to change surgical practice in women at general population risk for ovarian cancer and perform bilateral salpingectomy at the time of hysterectomy without oophorectomy and in lieu of tubal ligation, a practice that has been termed opportunistic salpingectomy (OS). Despite suggestions that bilateral salpingectomy may be used as an interim procedure in women with BRCA1/2 mutations, enabling them to delay oophorectomy, there is insufficient evidence to support this practice as a safe alternative and risk-reducing bilateral salpingo-oophorectomy remains the recommended standard of care for high-risk women. While evidence on uptake of OS is sparse, it points toward increasing practice of OS during hysterectomy. The practice of OS for sterilization purposes, although expanding, appears to be less common. Operative and perioperative complications as measured by administered blood transfusions, hospital length of stay and readmissions were not increased with the addition of OS either at time of hysterectomy or for sterilization. Additional operating room time was 16 and 10 min for OS with hysterectomy and OS for sterilization, respectively. Short-term studies of the consequences of OS on ovarian function indicate no difference between women undergoing hysterectomy alone and hysterectomy with OS, but no long-term data exist. There is emerging evidence of effectiveness of excisional sterilization on reducing ovarian cancer rates from Rochester (OR = 0.36 95 % CI 0.13, 1.02), and bilateral salpingectomy from Denmark (OR = 0.58 95 % CI 0.36, 0.95) and Sweden (HR = 0.35, 95 % CI 0.17, 0.73), but these studies suffer from limitations, including that they were performed for pathological rather than prophylactic purposes. Initial cost-effectiveness modeling indicates that OS is cost-effective over a wide range of costs and risk estimates. While preliminary safety, efficacy, and cost-effectiveness data are promising, further research is needed (particularly long-term data on ovarian function) to firmly establish the safety of the procedure. The marginal benefit of OS compared with tubal ligation or hysterectomy alone needs to be established through large prospective studies of OS done for prophylaxis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".