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Record W3201949467 · doi:10.30683/1927-7229.2019.08.06

Preoperative HE4 Tumor Marker and Prognostic Factors in Endometrial Cancer: Review Article

2019· article· en· W3201949467 on OpenAlexvenueno aff
Andrea Espiau Romera, Laura Baquedano, M.J. Puente Luján, R. Laborda Gotor, Leyre Ruiz Campo, Miguel Ángel Ruiz Conde

Bibliographic record

VenueJournal of Analytical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEndometrial cancerTumor markerOncologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Purpose of the Review: The aim of the review is to summarize the current evidence of HE4 tumor marker as a prognostic marker of endometrial cancer since it is a novel and not yet validated marker in the management of this neoplasm. Recent Findings: HE4 has been studied as a preoperative prognosis marker and the result is encouraging as it is statistically related to unfavorable prognostic markers in endometrial cancer. Having a preoperative marker that relates with prognosis is a non invasive and cost-effective way to classify the patients before the surgery act. Summary: Clinicians could use HE4 as a prognostic marker to help them in the preoperative decision-making process. Thus, good prognostic patients with a low serum HE4 could have a less invasive surgery avoiding lymphadecnectomy which decrease the morbidity of the procedure and reducing the operative time.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.367
Teacher spread0.333 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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