Prognostic Effect of Basal-Like Breast Cancers Is Time Dependent: Evidence from Tissue Microarray Studies on a Lymph Node–Negative Cohort
Bibliographic record
Abstract
PURPOSE: To determine whether data obtained from tissue microarrays (TMA) of a prospectively accrued node-negative breast cancer cohort are prognostically informative, we compared data derived from TMA with previously determined molecular markers. Subsequent to this validation, we examined outcome in specific subgroups defined using TMA data. EXPERIMENTAL DESIGN: A consecutive series of 1,561 patients were followed for recurrence (median follow-up of 107 months). Estrogen receptor, progesterone receptor, p53, and HER2 expression, examined using TMA constructed from 887 tumors, was compared with status evaluated previously by biochemical and molecular methods. The associations with risk of recurrence were examined for biomarkers as well as for HER2, luminal, and basal subgroups defined by immunohistochemical expression. RESULTS: In line with earlier molecular studies, a significant risk of recurrence was found in patients with HER2 overexpression (relative risk = 2.30; P = 0.002) and p53-positive tumors (relative risk = 1.81; P = 0.005) in univariate Cox model analysis. Although complete concordance between methodologies was not observed for estrogen receptor and progesterone receptor, their associations with disease-free survival were consistent with established prognostic findings. Patients with basal-type tumors fared worse within 36 months of diagnosis but not thereafter. CONCLUSIONS: This study shows the clinical validity of TMA in evaluating the importance of prognostic markers in this cohort. Furthermore, it shows a marked time-dependent effect in tumor subgroups, most notable within the basal subgroup. Our data suggest that patients with basal-like tumors may be broadly separable into two clinically distinctive groups: those likely to experience disease recurrence in the short term and those that will experience long-term survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".