Serum Carcinoembryonic Antigen as a Tumour Marker in Patients with Endometrial Cancer
Bibliographic record
Abstract
Background: No potential tumour markers have been validated for prognosis in endometrial cancer. However, carcinoembryonic antigen (CEA) is one of the most widely used tumour markers in various types of cancer. Although CEA expression in endometrial cancer has been investigated, its prognostic value remains controversial, and no studies have investigated serum CEA levels in large case series. In the present study, we investigated diagnostic and prognostic applications of serum CEA for endometrial cancer. Methods: This prospective study was approved by our Institutional Review Board. Between January 2006 and December 2012, serum CEA was measured prospectively in 215 patients with endometrial cancer and was subsequently measured during treatment and at scheduled follow-up examinations in patients with elevated baseline serum CEA. Results: During the study period, 215 patients (142 stage I, 19 stage II, 32 stage III, 22 stage IV) were treated for endometrial cancer. By the time of last follow-up, 52 had relapsed (24.2%), and the median follow-up duration was 45 months (range: 1–95 months). Elevated serum CEA was identified in 25 patients (11.6%) and was associated with histologic type (p = 0.04), histologic grade (p = 0.03), and myometrial invasion depth (p = 0.01). Elevated serum CEA was not related to clinical stage, lymph node metastasis, distant metastasis, age, menopausal status, or body mass index. Relapse of disease was related to elevated serum CEA (p = 0.006). Conclusions: Serum CEA is a potential prognostic indicator for endometrial cancer.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".