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Early Recurrence of Ovarian Serous Borderline Tumor as High-grade Carcinoma: A Report of Two Cases

2004· article· en· W1979901429 on OpenAlexaff
Robin Parker, Philip B. Clement, David J. Chercover, Thangaraja Sornarajah, C. Blake Gilks

Bibliographic record

VenueInternational Journal of Gynecological Pathology · 2004
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSerous fluidMedicineSerous carcinomaStage (stratigraphy)Clear cell carcinomaCarcinomaOvarian carcinomaLymph nodePathologyOvarian cancerCancerInternal medicine

Abstract

fetched live from OpenAlex

Ovarian serous borderline tumors (SBTs) are characteristically associated with an indolent course. Recurrences are often delayed and usually show morphologic features of SBT or low-grade serous carcinoma. Transformation to high-grade carcinoma has rarely been documented. We report 2 cases of ovarian SBTs that recurred early as high-grade carcinomas. The first was a 50-year-old woman treated surgically and with chemotherapy for a FIGO stage 1C SBT with microinvasion, who experienced a recurrence in an axillary lymph node at 27 months. The recurrent tumor consisted of well-differentiated papillary serous tumor that resembled the primary tumor and poorly differentiated serous carcinoma. The patient died of progressive disease 43 months after her initial presentation. The second case was a 61-year-old woman treated surgically and with chemotherapy for a stage 3C micropapillary SBT with noninvasive implants. Eighteen months later, an incisional hernia was found that contained high-grade sarcomatoid-type carcinoma with microscopic foci of better differentiated tumor that resembled the primary SBT. This patient is alive with disease 24 months after her initial presentation. Whereas the malignant potential of SBTs remains controversial, the cases described herein demonstrate that SBTs can behave unpredictably and may rarely transform into high-grade carcinoma.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.295
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.028
GPT teacher head0.333
Teacher spread0.305 · 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

Citations56
Published2004
Admission routes1
Has abstractyes

Explore more

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