Prognostic value of pretreatment circulating neutrophils, monocytes, and lymphocytes in oropharyngeal cancer stratified by human papillomavirus status
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to investigate the prognostic value of the pretreatment circulating neutrophil count (CNC), circulating monocyte count (CMC), and circulating lymphocyte count (CLC) in human papillomavirus (HPV)-related (HPV+) and HPV-unrelated (HPV-) oropharyngeal cancer (OPC). METHODS: All p16-confirmed HPV+ and HPV- OPC cases treated with chemoradiotherapy from 2000 to 2010 were included. Overall survival (OS) and recurrence-free survival (RFS) were compared for high and low CNCs, CMCs, and CLCs (dichotomized by median values). A multivariate analysis (MVA) confirmed their prognostic value in HPV+ and HPV- tumors, respectively. RESULTS: Five hundred ten HPV+ OPC cases and 192 HPV- OPC cases were included. The HPV+ cohort had lower CNC and CMC values but a CLC similar to that of the HPV- patients (P < .01). The median follow-up was 4.8 years. In the HPV+ cohort, a high CNC or CMC correlated with reduced OS and RFS in comparison with a low CNC or CMC (P < .01 for all), but no difference was evident in OS (P = .30) or RFS (P = .10) with the CLC. MVA confirmed that a higher CNC or CMC independently predicted lower OS (hazard ratio [HR] for CNC, 1.14, P < .01; HR for CMC, 2.95, P < .01) and lower RFS (HR for CNC, 1.11, P < .01; HR for CMC, 3.39, P < .01), whereas a higher CLC was associated with higher RFS (HR, 0.66, P = .03) and marginally higher OS (HR, 0.80, P = .08). In the HPV- cohort, CNC, CMC, and CLC were not predictive of OS (P = .16, P = .86, and P = .14) or RFS (P = .61, P = .59, and P = .62). CONCLUSIONS: This relatively large cohort study demonstrates that a high CNC and a high CMC independently predict inferior OS and RFS, whereas a high CLC predicts better RFS and marginally better OS in HPV+ OPC patients. This association was not apparent in HPV- patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".