Clinical Significance of Grade 1 Triple Negative Breast Cancer: A retrospective cohort analysis
Bibliographic record
Abstract
Grade 1 TNBCs comprise of histologically low-grade lesions whose natural histories, molecular features, and optimal therapy vary from those of high-grade TNBCs. Here, we describe the clinopathologic features and outcomes of patients with Grade 1 TNBC. This is a retrospective cohort study on Grade 1 TNBC patients from two separate Regional Cancer Programs in Canada seen from January 1, 2004 to December 31, 2022 . Demographic data, tumor characteristics, treatment and outcome of patients with TNBC from the two institutions were collected and analyzed. We identified a different pattern of histology for Grade 1 TNBC where 17 of 19 (89.4%) patients had infiltrating ductal disease, in contrast to literature which reported either carcinoma with salivary gland like morphology or low grade lesions considered benign as the more common histology pattern. Five had breast cancer recurrence indicating a recurrence rate of 26.3%. Out of the 5 patients with recurrence, one was stage 3, three were stage 2 and one was stage 3. All three patients (15.7%) who died from cancer were stage 2. TNBC patients with grade 1 tumors in this study were shown to have a different histology from that reported in literature and more similar to other grades of TNBC. The study also showed recurrence rate in more than a quarter of the cases . The relapse pattern is not dissimilar to other grades of TNBC and according to this study does not represent a unique subset of TNBC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".