Anemia, leukocytosis and thrombocytosis as prognostic factors in patients with cervical cancer treated with radical chemoradiotherapy: A retrospective cohort study
Bibliographic record
Abstract
Introduction Anemia has long been associated with poor prognosis in patients with cervical cancer. Recently, additional hematologic parameters have emerged as potential indicators of worse outcome in this patient group. In a cohort of cervical cancer patients treated with chemoradiotherapy (CRT) and brachytherapy, we report on the prognostic significance of hematologic parameters including anemia, leukocytosis, neutrophil to lymphocyte ratio (NLR), and thrombocytosis, the effect of combining anemia with other hematologic parameters, and the effect of changes in hemoglobin levels during treatment. Materials and methods Two-hundred fifty-seven cervical cancer patients were retrospectively identified from a single cancer institution's database. Hematologic parameters were categorized as: anemia (hemoglobin ≤115g/L), leukocytosis (white blood cell count >10×10 9 /L), thrombocytosis (platelets >400×10 9 /L), and NLR (ratio >5). The association between clinical factors and hematologic parameters on progression-free survival (PFS) and overall survival (OS) were assessed at 5years. Results At 5years, both pre-treatment anemia (PFS: 60% vs 34%, p <0.0001; OS: 68% vs 41%, p <0.0001) and on-treatment anemia (PFS: 62% vs 40%, p <0.0001; OS: 70% vs 48%, p <0.0001) were significantly associated with worse survival. This adverse effect on 5-year PFS and OS was increased in patients with both pre-treatment anemia and leukocytosis (PFS: 72% vs 42%, p <0.0001; OS: 68% vs 37%, p <0.0001) and pre-treatment anemia and elevated NLR (PFS: 61% vs 30%, p <0.0001; OS: 68% vs 37%, p <0.0001). Five-year PFS (50% vs 31%) and OS (60% vs 36%) was better in patients whose pre-treatment anemia improved to normal hemoglobin levels on treatment vs those patients who were anemic both pre- and on-treatment. Conclusion Pre-treatment and on-treatment anemia were significant, independent predictors of worse PFS and OS. Anemia and other hematologic parameters remain prognostic markers for cervical cancer patients. Improvement in PFS and OS was seen in patients with normalization of hemoglobin.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".