Prognostic value of CD8<sup>+</sup> tumor‑infiltrating T cells in patients with breast cancer: A systematic review and meta‑analysis
Bibliographic record
Abstract
CD8+ tumor‑infiltrating lymphocytes have been regarded as potential biomarkers for cancer prognosis, while the prognostic effect of CD8+ tumor‑infiltrating T cells remains controversial in breast cancer. In the present study, a meta‑analysis was performed to evaluate the prognostic value of CD8+ T cells in breast cancer and the associations between CD8+ T cells and the pathological characteristics. The PubMed, Embase and the Cochrane Library were systematically searched entries added from the establishment of the database to November 2021 and prospective or retrospective studies of patients with breast cancer were included. The Newcastle‑Ottawa Scale was used to assess the quality of evidence for each study. STATA 15.1 was used for the data analysis. A total of 14 studies comprising 22,222 patients were included in the final analysis and the pooled results suggested that a high CD8+ T‑cell infiltration level was significantly related to better overall survival [hazard ratio (HR)=0.70, 95% confidence interval (CI): 0.60‑0.82, P<0.001] and disease‑free survival (HR=0.63, 95% CI: 0.49‑0.81, P<0.001) for patients with breast cancer. In addition, a high CD8+ T‑cell infiltration level was significantly associated with decreased expression of estrogen receptor [odds ratio (OR)=1.92, 95% CI: 1.30‑2.85, P=0.001] and progesterone receptor (OR=1.66, 95% CI: 1.14‑2.42, P=0.008), and increased human epidermal growth factor receptor 2 expression (OR=0.79, 95% CI: 0.66‑0.94, P=0.010) in patients with breast cancer, while there was no significant association between CD8+ T‑cell infiltration and age, tumor size or lymph node status of patients with breast cancer (P>0.05). In conclusion, CD8+ T‑cell infiltration is of prognostic value in patients with breast cancer. High levels of CD8+ T‑cell infiltration were related to improved prognosis, including OS and DFS, in patients with breast cancer.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".