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Record W2908657103 · doi:10.1097/pgp.0000000000000518

Endometrial Carcinoma Diagnosis: Use of FIGO Grading and Genomic Subcategories in Clinical Practice: Recommendations of the International Society of Gynecological Pathologists

2018· review· en· W2908657103 on OpenAlexaff
Robert A. Soslow, Carmen Tornos, Kay J. Park, Anaís Malpica, Xavier Matías‐Guiu, Esther Oliva, Vinita Parkash, Joseph W. Carlson, W. Glenn McCluggage, C. Blake Gilks

Bibliographic record

VenueInternational Journal of Gynecological Pathology · 2018
Typereview
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsVancouver General HospitalUniversity of British Columbia
FundersNational Cancer Institute
KeywordsMedicineGrading (engineering)CarcinomaHysterectomyGynecologyObstetrics and gynaecologyEndometrial cancerOncologyObstetricsInternal medicineCancerRadiologyPregnancyBiology

Abstract

fetched live from OpenAlex

In this review, we sought to address 2 important issues in the diagnosis of endometrial carcinoma: how to grade endometrial endometrioid carcinomas and how to incorporate the 4 genomic subcategories of endometrial carcinoma, as identified through The Cancer Genome Atlas, into clinical practice. The current International Federation of Gynecology and Obstetrics grading scheme provides prognostic information that can be used to guide the extent of surgery and use of adjuvant chemotherapy or radiation therapy. We recommend moving toward a binary scheme to grade endometrial endometrioid carcinomas by considering International Federation of Gynecology and Obstetrics defined grades 1 and 2 tumors as "low grade" and grade 3 tumors as "high grade." The current evidence base does not support the use of a 3-tiered grading system, although this is considered standard by International Federation of Gynecology and Obstetrics, the American College of Obstetricians and Gynecologists, and the College of American Pathologists. As for the 4 genomic subtypes of endometrial carcinoma (copy number low/p53 wild-type, copy number high/p53 abnormal, polymerase E mutant, and mismatch repair deficient), which only recently have been identified, there is accumulating evidence showing these categories can be reproducibly diagnosed and accurately assessed based on biopsy/curettage specimens as well as hysterectomy specimens. Furthermore, this subclassification system can be adapted for current clinical practice and is of prognostic significance independent of conventional variables used for risk assessment in patients with endometrial carcinoma (eg, stage). It is too soon to recommend the routine use of genomic classification in this setting; however, with further evidence, this system may become the basis for the subclassification of all endometrial carcinomas, supplanting (partially or completely) histotype, and grade. These recommendations were developed from the International Society of Gynecological Pathologists Endometrial Carcinoma project.

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)0.019
metaresearch head score (Gemma)0.033
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: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.005
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0040.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.002

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 head0.193
GPT teacher head0.446
Teacher spread0.253 · 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
GenreReview

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

Citations317
Published2018
Admission routes1
Has abstractyes

Explore more

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