Prognostic Significance of Disseminated Tumor Cells in Bone Marrow for Endometrial Carcinoma Patients
Bibliographic record
Abstract
Background: Until now, limited clinical significance had been reported for disseminated tumor cells (DTCs) in gynecologic malignancies. DTCs were previously reported not to be associated with established risk factors, L1CAM immunoreactivity, and outcome in endometrial carcinoma (EC). This study’s primary objective was to investigate potential correlations of DTCs in the bone marrow (BM) of EC patients with disease-related survival, and a secondary objective was to evaluate associations between molecular classification of EC and DTCs. Methods: Patients treated for primary EC at Tuebingen University women’s hospital between 2003 and 2016 were identified. A total of 402 patients with a complete set of BM cytology, molecular, and clinical data were evaluable. Results: DTC occurrence was distributed equally among all four molecular groups (p = 0.651). DTC positivity was associated with a less favorable disease-free survival (HR: 1.86, 95% CI: 1.03–3.36, p = 0.036) and progression-free survival (HR: 1.86, 95% CI: 1.01–3.44, p = 0.045). Presence of DTCs was associated with a higher frequency of distant disease recurrence (p = 0.017). Conclusions: In line with our previous findings, tumor cell dissemination is not associated with molecular features in our large cohort of primary EC patients. Since DTCs seem to be associated with survival and location of disease recurrence, further studies are needed to decisively define their role in EC survival.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".