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Record W4410816600 · doi:10.1016/j.ijgc.2025.101957

Co-existent endometrial and ovarian carcinoma: molecular and pathological features define low risk entity

2025· article· en· W4410816600 on OpenAlexafffund
Amy Jamieson, Jutta Huvila, Samuel Leung, Marcel Grube, Andrea Neilson, Niki Boyd, Derek S. Chiu, Mehrane Nazeran, Michael S. Anglesio, Janine Senz, Amy Lum, Stefan Kommoss, David G. Huntsman, C. Blake Gilks, Jessica N. McAlpine

Bibliographic record

VenueInternational Journal of Gynecological Cancer · 2025
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsUniversity of British Columbia
FundersBC Cancer FoundationVancouver Coastal Health Research Institute
KeywordsMedicinePathologicalCarcinomaOncologyGynecologyOvarian carcinomaInternal medicineOvarian cancerCancer

Abstract

fetched live from OpenAlex

OBJECTIVE: Most co-existent endometrial and ovarian carcinomas are clonally related and exhibit an indolent disease course. Pathologic assignment and clinical management of this entity vary greatly. The International Federation of Gynecology and Obstetrics (FIGO) 2023 endometrial carcinoma staging/risk stratification system introduced a new substage for co-existent endometrial and ovarian carcinomas that meet strict pathologic criteria (stage IA3, distinct from IIIA1). Our aim was to validate if FIGO IA3 identifies a subset of co-existent endometrial and ovarian carcinomas at very low risk of recurrence and determine whether further refinement, through molecular features and expanded ovarian pathologic criteria, could improve prognostic discernment and direct more patients for consideration of de-escalation. METHODS: Clinicopathologic, molecular, and outcome data were collected on patients with co-existent endometrial and ovarian carcinoma, extracted from pathology archives and molecularly classified endometrial carcinoma cohorts. RESULTS: Among the 154 co-existent endometrial and ovarian carcinoma patients, higher recurrence rates were observed with the p53abn (2/6, 33%), mismatch repair deficiency (MMRd) (7/34, 21%) or no specific molecular profile (NSMP) estrogen receptor (ER) negative-low (2/15, 13%) molecular sub-types, compared with patients with POLEmut or NSMP ER strong positive tumors. Thirty-two patients met FIGO IA3 criteria, with one recurrence and death event (MMRd). Eliminating patients with adverse molecular features (p53abn or MMRd endometrium or ovary, or NSMP ER negative-low endometrium) and expanding criteria to include any POLEmut or cases with bilateral ovarian involvement, intra- or pre-operative ovarian rupture, or ovarian surface involvement significantly improved risk stratification (p = .008) and added 48 co-existent endometrial and ovarian carcinoma patients (>2-fold increase) with no recurrence events (mean follow-up: 6 years). There was 91% concordance of molecular sub-type assignment between endometrial and ovarian tumors. CONCLUSIONS: FIGO IA3 criteria identify a subset of co-existent endometrial and ovarian carcinomas with excellent outcomes. However, incorporating molecular features into the definition enables greater prognostic discernment and supports the inclusion of patients with a broader range of pathologic features with indolent disease (increased from 20% to 49% of the cohort, 0 recurrences) who may be candidates for treatment de-escalation.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.327
Teacher spread0.312 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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