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Record W4391649405 · doi:10.1016/j.gore.2024.101334

Serous tubal intraepithelial carcinoma (STIC) outcomes in an average risk population

2024· article· en· W4391649405 on OpenAlexaffabout
Kimberly Stewart, Lien Hoang, Janice S. Kwon

Bibliographic record

VenueGynecologic Oncology Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineSerous carcinomaGenetic testingSerous fluidCohortInternal medicinePopulationCohort studyGynecologyOncologyOvarian cancerCancer

Abstract

fetched live from OpenAlex

Serous tubal intraepithelial carcinoma (STIC) are precursors for high grade serous carcinomas (HGSC) of tubo-ovarian origin. It is a rare entity, most commonly described in patients with a BRCA pathogenic variant (PV) undergoing risk-reducing surgery. Little is known about the risk of subsequent HGSC in patients found to have an isolated STIC without a genetic PV. The objective of this study is to report the outcomes of STIC diagnosed in patients with negative genetic testing (“average risk”). Retrospective population-based cohort study from British Columbia, Canada. Chart review of patients diagnosed with an isolated STIC from January 2012 to May 2022. Average risk patients are defined as individuals with known negative genetic testing results. Treatment and outcomes are described in the “average risk”, BRCA PV, and total cohorts. Twenty-nine patients with isolated STIC were identified. Ten patients had a BRCA PV, four had other variants identified (BRIP1, MLH1, BRIP1 VUS, BRCA 2 VUS), nine had no PV identified (“average risk”), and six were unknown (no genetic testing). Of the nine “average risk” patients, eight (89 %) underwent surgical staging. Three (33.3 %) had subsequent HGSC diagnosed 29, 70 and 86 months after STIC diagnosis. STIC identified in patients with negative genetic testing are at risk of subsequent HGSC. Patients developed primary peritoneal HGSC despite surgical staging. These patients should also be included in future meta-analysis to determine outcomes and optimal treatment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.087
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.327
Teacher spread0.309 · 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 teacher head, 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

Citations7
Published2024
Admission routes2
Has abstractyes

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