Validation of Intratumoral T-bet+ Lymphoid Cells as Predictors of Disease-Free Survival in Breast Cancer
Bibliographic record
Abstract
We previously observed T-bet(+) lymphocytes to be associated with a good prognosis in a cohort of women with familial breast cancer. To validate this finding, we evaluated lymphocyte T-bet expression in an independent unselected prospectively accrued series of women with lymph node-negative breast carcinoma. T-bet and clinicopathologic data were available for 614 women. Hormone receptors, HER2, Ki-67, CK5, EGFR, p53, and T-bet status were determined using IHC and/or biochemical methods. Tumors were assigned to luminal A, luminal B, HER2, and basal subtypes based on the expression of IHC markers. Multiple cutpoints were examined in a univariate penalized Cox model to stratify tumors into T-bet(+/high) and T-bet(-/low). Fisher exact test was used to analyze T-bet associations with clinicopathologic variables, IHC markers, and molecular subtype. Survival analyses were by the Cox proportional hazards model. All tests were two sided. A test with a P value < 0.05 was considered statistically significant. T-bet(+/high) tumor status was significantly associated with large tumor size, high grade, hormone receptor negativity, CK5, EGFR and p53 positivity, high Ki-67, and basal subtype. With a median follow-up of 96.5 months, T-bet(-/low) tumor status was associated with a reduced disease-free survival compared with T-bet(+/high) tumor status in multivariate analysis (P = 0.0027; relative risk = 5.62; 95% confidence intervals, 1.48-50.19). Despite being associated with adverse clinicopathologic characteristics, T-bet(+) tumor-infiltrating lymphoid cells are associated with a favorable outcome. This supports their role in Th1-mediated antitumor activity and may provide insight for the development of new therapeutic strategies.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Validation of T-bet positive lymphoid cells as a prognostic biomarker in breast cancer; 'validation' here is clinical biomarker confirmation, the polysemy trap, and the object is prognosis.
The term validation refers to confirming a cancer biomarker's prognostic association, not studying research validation practices.
Clinical biomarker validation of T-bet+ cells for breast-cancer prognosis; polysemy of validation, domain oncology.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".