Impact of radiation related lymphopenia on outcomes in esophageal cancer: a systematic review and meta-analysis of clinical studies
Bibliographic record
Abstract
Background: Esophageal cancer (EC) has an aggressive cancer biology with relatively poor outcomes with a 5-year survival rate of 15–25%. Radiation forms an integral part of the treatment paradigm with utility in neoadjuvant, adjuvant and definitive settings to improve survival. Recent data has shown that depletion of circulating lymphocyte populations is associated with suboptimal tumor control and inferior overall survival outcomes. Methods: This systematic review and pooled analysis of studies was done to better understand the impact of radiation associated lymphopenia on overall survival and progression free survival in EC. The study was done according to PRISMA guidelines, and the quality of studies were assessed by Newcastle Ottawa scale. Results: The systematic search of PubMed, EMBASE and Cochrane library resulted in 2,969 abstracts. Twenty studies were included in the systematic review and 5 studies were included in the meta-analysis. Larger planning target volume (PTV) volume, use of photon beam instead of proton beam for treatment and higher estimated dose to immune cells (EDIC) were consistently associated with higher rates of severe lymphopenia. The analyses of dose to spleen on lymphopenia provided varied results with studies showing both higher and lower risk of lymphopenia with higher splenic doses. Patients with severe lymphopenia were at increased risk of death with a pooled hazard ratio (HR) =1.57 [95% confidence interval (CI): 1.35–1.83, I2=0%, P<0.00001] compared to patients with no severe lymphopenia. Patients with severe lymphopenia were at increased risk of progression with a pooled HR =1.42 (95% CI: 1.19–1.70, I2=0%, P<0.0001). Conclusions: Severe lymphopenia with chemo-radiotherapy (CRT) is associated with worse overall survival and increased risk of disease recurrence. Larger PTV, higher EDIC result in higher risk of severe lymphopenia.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.043 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".