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Performance of preoperative plasma HE4 and CA-125 levels in predicting ovarian cancer mortality in women with epithelial ovarian cancer (EOC).

2017· article· en· W2891080378 on OpenAlexaffabout
Isabelle Bairati, Jean‐Pierre Grégoire, Marie Plante, Pierre Douville

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineCohortInternal medicineReceiver operating characteristicOncologyBiomarkerOvarian cancerDebulkingCancerYouden's J statistic

Abstract

fetched live from OpenAlex

e17076 Background: Additional prognostic biomarkers are needed to better manage women with EOC, especially dichotomized indicators for decision making. The objective of this external validation study was to assess the performance of preoperative plasma HE4 and CA-125 levels in predicting mortality by EOC. Methods: Eligible EOC women were newly diagnosed cases treated by upfront debulking surgery in a gynecology oncology center (CHU de Québec, L’Hôtel-Dieu, Canada) in 1988-2006 (cohort 1, n=136) and in 2007-2013 (cohort 2, n=177). All FIGO stages were included. Preoperative plasma HE4 and CA-125 levels were measured by Elecsys® automated immunoassay (Roche Diagnostics). Dates and causes of death were obtained by record linkage with the Quebec mortality files. In cohort 1, time-dependent receiver operating characteristic (ROC) curves were performed and optimal thresholds for HE4 and CA-125 were generated using the Youden index J. In cohort 2, crude and standardized Cox proportional models were done to validate the usefulness of these biomarkers according to their optimal thresholds. Standardized models included standard prognostic factors. The Likelihood Ratio (LR) tests were done to compare the standardized models with and without each biomarker. Results: In cohorts 1 and 2, medians of follow-up were respectively 5.3 and 3.2 years. Five-year disease free survival rates were 53% in cohort 1 and 54% in cohort 2. In cohort 1, the AUC for HE4 and CA-125 were respectively 64.2 (95% CI: 54.7-73.6) and 63.1 (95%CI: 53.6-72.6). The optimal thresholds were 277 pmol/L for HE4 and 282 U/ml for CA-125. In cohort 2, higher levels of plasma HE4 (≥277 pmol/L) were significantly associated with death by EOC (adjusted hazard ratio (aHR): 1.80; 95% CI: 1.03-3.15; p-value for LR test: 0.03), while higher levels of CA-125 (≥282 U/ml) were not associated with death by EOC (aHR: 1.50; 95% CI: 0.88-2.55; p-value for LR-test: 0.12). In serous EOC, the associations with mortality were respectively 2.46 (95% CI: 1.26-4.80) for HE4 and 1.56 (0.87-2.80) for CA-125. Conclusions: Preoperative plasma HE4 is a promising prognostic biomarker in women with EOC and performs better than CA-125 to predict mortality.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.115
GPT teacher head0.451
Teacher spread0.336 · 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".

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Citations2
Published2017
Admission routes2
Has abstractyes

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