Anaemia, blood transfusions and survival in high-grade endometrial cancer: retrospective study
Bibliographic record
Abstract
OBJECTIVE: To determine if anaemia and blood transfusions in the perioperative, chemotherapy and radiation treatment periods are associated with overall survival (OS) and recurrence-free survival (RFS) in high-grade endometrial cancer. METHODS: This retrospective cohort study examined patients at a single centre treated for high-grade endometrial cancer (2010-2023). This included International Federation of Gynecology and Obstetrics (FIGO) grade 3 endometrioid, serous, carcinosarcoma, mixed, clear cell, mucinous, dedifferentiated and undifferentiated histology. Primary outcomes were OS and RFS. Predictor variables were nadir haemoglobin and transfusion status. Multivariable Cox regression models for OS and RFS analysed the associations of treatment period-specific anaemia, overall transfusion status and confounder variables. RESULTS: Two hundred twenty-seven cases were included; 64-86% of patients were anaemic during any treatment, with 0-10% having severe anaemia. Twenty-two patients (9.7%) had at least one blood transfusion. Transfusion in the perioperative and chemotherapy periods was associated with poorer survival, significant only for shorter RFS in the chemotherapy cohort (HR 3.22, p=0.04). There was no association between anaemia and survival. CONCLUSION: This study is among the first to assess anaemia in treated patients with high-grade endometrial cancer and the associations of anaemia and blood transfusion with survival outcomes. Further larger studies are needed to strengthen evidence and guide transfusion policies.
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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 | 0.001 | 0.003 |
| 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".