Change in <scp>CD</scp>3ζ‐chain expression is an independent predictor of disease status in head and neck cancer patients
Bibliographic record
Abstract
CD3ζ has emerged as a clinically important immunological marker in head and neck squamous cell carcinoma (HNSCC) with reduced level of expression reported in both tumor infiltrating lymphocytes and peripheral blood lymphocytes. In this prospective study (power = 0.99, α = 0.05), CD3ζ expression was compared in 47 HNSCC patients and 53 controls using standardized flow cytometric method. There was no statistical difference in the percentages of the CD3 ε+ T-cell subset present in the peripheral blood mononuclear cells of the HNSCC patients and the healthy controls; however, T cells from the HNSCC patients produced a significantly weaker IFN-γ response in comparison to the healthy controls, when they were stimulated by the recall viral CEF peptide antigen. All patients were followed up for at least 3 years with a median follow-up of 45 months. Levels of CD3ζ-chain expression were measured at 117 follow-up visits at six-month intervals. Receiver operating characteristic curve identified the optimal cut off as a 12% increase in post treatment CD3ζ-chain expression from the baseline levels to confirm absence of HNSCC with the area under curve of 0.81 (95% CI = 0.68-0.94) for predicting absence of HNSCC. The specificity, sensitivity and positive predictive value were 81.25% 79.21% and 97.56%, respectively. Three-year disease specific survival (DSS) was significantly lower (p = 0.007) at 63.2% for patients who showed <12% increase in CD3ζ-chain level as compared to 96.2% for patients who had ≥12% increase. Our results indicate that the change in CD3ζ-chain expression from the baseline is an independent predictor of residual and recurrent HNSCC.
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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 | 0.001 |
| 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".