Prognostic Significance of Blood Transfusions in Patients With Esophageal Cancer Treated With Combined Chemoradiotherapy
Bibliographic record
Abstract
OBJECTIVE: Anemia occurs commonly in patients with esophageal cancer. This study evaluates the effect of blood transfusion on survival outcomes in patients with esophageal cancer treated with combined chemoradiotherapy (CRT). PATIENTS AND METHODS: Fifty-six consecutive patients with unresectable esophageal cancer received 50 Gy in 25 fractions over 5 weeks concurrent with cycles 2 and 3 of cisplatin and 5-fluorouracil chemotherapy. Data on hemoglobin before and during radiation therapy (RT) and blood transfusion use were abstracted by chart review. Each patient had a blood count before every chemotherapy cycle, and the test was repeated if the blood count was low. Five-year Kaplan-Meier overall survival (OS) and relapse-free survival (RFS) estimates were compared according to pre-RT hemoglobin levels and transfusion use. Multivariate analysis using Cox regression modeling was performed to determine the prognostic significance of pre-RT hemoglobin and transfusion use on survival outcomes. RESULTS: The 5-year OS and RFS rates were 30% and 37%, respectively. Seventeen patients (30%) received transfusions during CRT. Among 18 patients (32%) with a hemoglobin of < or =12 g/dL at the start of RT, 9 received transfusions. Pre-RT hemoglobin levels of < or =12 g/dL were strongly associated with the use of blood transfusions (P = 0.03). Five-year Kaplan-Meier OS was 65% versus 21% in patients treated with, versus without, a transfusion (P = 0.006). On multivariate analysis, the use of blood transfusion was associated with improved OS (hazard ratio, 0.26; 95% confidence interval, 0.09-0.75, P = 0.01). CONCLUSIONS: The use of blood transfusion is a significant treatment-related factor associated with improved survival in patients undergoing CRT for esophageal cancer.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".