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Record W3203701277 · doi:10.1016/j.ajog.2021.09.020

Ovarian cancer incidence and death in average-risk women undergoing bilateral salpingo-oophorectomy at benign hysterectomy

2021· article· en· W3203701277 on OpenAlexafffundabout
Maria C. Cusimano, Sarah E. Ferguson, Rahim Moineddin, Maria Chiu, Suriya Aktar, Ning Liu, Nancy N. Baxter

Bibliographic record

VenueAmerican Journal of Obstetrics and Gynecology · 2021
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsInstitute for Clinical Evaluative SciencesSinai Health SystemPrincess Margaret Cancer CentrePublic Health OntarioUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchCancer Care OntarioAmerican College of Surgeons
KeywordsMedicineHysterectomyInterquartile rangeHazard ratioOvarian cancerGynecologyOophorectomyIncidence (geometry)PopulationObstetricsCancerConfidence intervalSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Opportunistic bilateral salpingo-oophorectomy is often offered to patients undergoing benign hysterectomy to prevent ovarian cancer, but the magnitude of risk reduction obtained with bilateral salpingo-oophorectomy in this population remains unclear and must be weighed against potential risks of ovarian hormone deficiency. OBJECTIVE: This study aimed to quantify the relative and absolute risk reduction in ovarian cancer incidence and death associated with bilateral salpingo-oophorectomy at the time of benign hysterectomy. STUDY DESIGN: We performed a population-based cohort study of all adult women (≥20 years) undergoing benign hysterectomy from 1996 to 2010 in Ontario, Canada. Patients with ovarian pathology, previous breast or gynecologic cancer, or evidence of genetic susceptibility to malignancy were excluded. Inverse probability of treatment-weighted Fine-Gray subdistribution hazard models were used to quantify the effect of bilateral salpingo-oophorectomy on ovarian cancer incidence and death while accounting for competing risks and adjusting for demographic characteristics, gynecologic conditions, and comorbidities. Analyses were performed in all women and specifically in women of postmenopausal age (≥50 years) at the time of hysterectomy. RESULTS: We identified 195,282 patients (bilateral salpingo-oophorectomy, 24%; ovarian conservation, 76%) with a median age of 45 years (interquartile range, 40-51 years). Over a median follow-up of 16 years (interquartile range, 12-20 years), 548 patients developed ovarian cancer (0.3%), and 16,170 patients (8.3%) died from any cause. Bilateral salpingo-oophorectomy was associated with decreased ovarian cancer incidence (hazard ratio, 0.23; 95% confidence interval, 0.14-0.38; P<.001) and decreased ovarian cancer death (hazard ratio, 0.30; 95% confidence interval, 0.16-0.57; P<.001). At 20 years follow-up, the weighted cumulative incidences of ovarian cancer were 0.08% and 0.46% with bilateral salpingo-oophorectomy and ovarian conservation, respectively, yielding an absolute risk reduction of 0.38% (95% confidence interval, 0.32-0.45; number needed to treat, 260). After restricting to women aged ≥50 years at hysterectomy, the absolute risk reduction was 0.62% (95% confidence interval, 0.47-0.77; number needed to treat, 161). CONCLUSION: Bilateral salpingo-oophorectomy resulted in a significant absolute reduction in ovarian cancer among women undergoing benign hysterectomy. Population-average risk estimates derived in this study should be balanced against other potential implications of bilateral salpingo-oophorectomy to inform practice guidelines, patient decision-making, and surgical management.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.265
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2021
Admission routes3
Has abstractyes

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