Prognostic significance of CD8+ T lymphocytes in breast cancer depends upon both oestrogen receptor status and histological grade
Bibliographic record
Abstract
AIMS: Results of previous studies on the influence of tumour infiltrating lymphocytes on prognosis of women with breast cancer have been mixed. This study re-evaluates the role of tumour-infiltrating lymphocytes as a prognostic marker in women with breast cancer. METHODS AND RESULTS: Immunochemistry staining of CD8(+) T cells was performed on a tissue microarray of 1953 breast carcinomas. When all tumours were considered, no association between the lymphocyte count and patient survival was found. In univariate analysis, there was a reduced disease-specific survival for women with oestrogen receptor (ER)-positive tumours with high intraepithelial lymphocyte count (P=0.004). In those with ER-negative tumours, the disease-specific survival was improved when the intraepithelial, stromal and total lymphocyte counts were high, the total lymphocyte count also being an independent prognostic marker on multivariate analysis (P=0.031). When stratified by histological grade, on univariate analysis, the previously observed inferior outcome in women with high lymphocyte count and ER-positive tumours remained significant only if tumours were also of low grade, and the superior outcome in those with ER-negative tumours remained significant if tumours were also of high grade. CONCLUSIONS: Our results raise the possibility of different immune-tumour interactions based on ER status and histological grade.
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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 | 0.001 | 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".