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Abstract B045: Evaluating the effectiveness of opportunistic salpingectomy (OS) for the prevention of epithelial ovarian cancer

2025· article· en· W4414349338 on OpenAlexaff
Ramlogan Sowamber, A.P. van der Mei, Paramdeep Kaur, Julianne McLeod, Emily McKay, Alex Lukey, Jamie N. Bakkum‐Gamez, Natália Buza, Paul A. Cohen, Kyle M. Devins, Rhonda Farrell, Christine Garcia, C. Blake Gilks, Ellen L. Goode, Anjelica Hodgson, Brooke E. Howitt, Pei Hui, Jutta Huvila, Anthony N. Karnezis, Kianoosh Keyhanian, Mary Kinloch, Martin Köbel, F. Kommoss, Lawrence H. Kushi, Janice S. Kwon, Kara C. Long-Roche, Anaís Malpica, Jessica N. McAlpine, Dianne Miller, Esther Oliva, Andrea Palicelli, Aleksandra Paliga, Carlos Parra‐Herran, Celeste Leigh Pearce, Sharnel Perera, Jurgen M.J. Piek, Joseph T. Rabban, Robert Rome, Miranda Steenbeek, Rebecca Stone, Aline Talhouk, Kristin M. Tischer, Britton Trabert, Penelope M. Webb, John Zalcberg, Gillian E. Hanley, David G. Huntsman

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of CalgaryUniversity of SaskatchewanUniversity of OttawaVancouver General HospitalUniversity Health NetworkUniversity of British Columbia
Fundersnot available
KeywordsOvarian cancerSalpingectomyFallopian tubePopulationCohortEpithelial ovarian cancerPathological

Abstract

fetched live from OpenAlex

Abstract Introduction: The purpose of this study is to evaluate the effectiveness of opportunistic salpingectomy (OS), a procedure that aims to remove only the fallopian tubes of general population risk women, for the prevention of epithelial ovarian cancer. Currently, the method of prevention for individuals at high risk of ovarian cancer involves a bilateral salpingo-oophorectomy (BSO), a procedure that removes both the fallopian tubes and ovaries. However, this procedure is not recommended for individuals of the general population, who make up about 80% of ovarian cancers, due to negative health implications to the cardiovascular and skeletal systems because of surgically induced menopause. The effectiveness of the OS in preventing ovarian cancers and how the procedure impacts the histotype distribution of ovarian cancers remains unknown. Study Methods: This study uses a population-based approach and a case-based approach to determine the effectiveness of OS and its impact on histotype distribution, respectively. For the population-based analysis, we will search through clinical databases to acquire cases of individuals who have had an OS and a tumor. A control population who have their fallopian tubes in-tact will also be acquired. A cox-proportional hazard analysis will be performed to determine the effectiveness of the procedure. Using pathological records, the case-based ascertainment of tumors from individuals who have had an OS will be selected and reviewed for histotype confirmation. Fallopian tubes of these patients will also be reviewed for precursor lesions. This cohort will be compared to a historical histotype distribution of ovarian cancers. Results: For the population-based approach, we have to date, identified less than five serous ovarian cancers in individuals who have had an OS (n=40, 477). A comparator surgery was used as a control and showed 21 cancers. For the case-based approach, we have partnered with 23 collaborating institutions from around the world to identify tumors in individuals who have had an OS. We have identified 26 epithelial ovarian cancers, with the most lethal gynecological histotype, high grade serous carcinoma (HGSC), accounting for 23.1% of the total proportion of epithelial ovarian cancer cases (n=6/26). This is significantly less than the historical histotype distribution of HGSC, which is 69.3% (Fisher’s exact test, p<0.0001). One HGSC case had a precursor lesion called a serous tubal intraepithelial carcinoma (STIC) while reviewing fallopian tubes of this individual. TP53 mutation analysis on one HGSC tumor sample showed a frameshift mutation in TP53 (c229fs) with the tumor and the corresponding STIC staining negative for p53 protein expression by immunohistochemistry. Conclusion: This evidence demonstrates the effectiveness of opportunistic salpingectomy for the prevention of ovarian cancer and shows a histotype distribution shift, with the most lethal gynecological malignancy having a significant reduction in cases following the procedure. Citation Format: Ramlogan Sowamber, Alice J. Mei, Paramdeep Kaur, Julianne McLeod, Emily McKay, Alex Lukey, Jamie Bakkum-Gamez, Natalia Buza, Paul Cohen, Kyle Devins, Rhonda Farrell, Christine Garcia, Blake Gilks, Ellen Goode, Anjelica Hodgson, Brooke Howitt, Pei Hui, Jutta Huvila, Anthony Karnezis, Kianoosh Keyhanian, Mary Kinloch, Martin Köbel, Felix KF. Kommoss, Lawrence Kushi, Janice S. Kwon, Kara Long-Roche, Anais Malpica, Jessica N. McAlpine, Dianne Miller, Esther Oliva, Andrea Palicelli, Aleksandra Paliga, Carlos Parra-Herran, Celeste Leigh Pearce, Sharnel Perera, Jurgen M. Piek, Haiyan Qiu, Joseph Rabban, Robert Rome, Miranda Steenbeek, Rebecca Stone, Aline Talhouk, Kristin M. Tischer, Britton Trabert, Penelope M. Webb, John R. Zalcberg, Gillian E. Hanley, David G. Huntsman. Evaluating the effectiveness of opportunistic salpingectomy (OS) for the prevention of epithelial ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Ovarian Cancer Research; 2025 Sep 19-21; Denver, CO. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl):Abstract nr B045.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.189
GPT teacher head0.517
Teacher spread0.328 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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