Abstract PO3-03-09: Clinical Significance of Grade in Triple Negative Breast Cancer
Bibliographic record
Abstract
Abstract Triple negative breast cancer (TNBC) is a heterogeneous cancer type that lacks receptors for estrogen (ER), progesterone (PR), and human epidermal growth factor receptor-2 proteins (HER-2). An important prognostic factor for breast cancer patients is the tumour grade, which is the degree of cell proliferation or differentiation of the tumour cells from normal cells. In our initial study involving 305 TNBC patients from 2004-2017 at Windsor Regional Hospital Cancer Centre, we found a statistically significant difference between grade 2 and grade 3 patients, with grade 2 predicting significantly inferior progression-free and overall survival. In our initial study, the overall survival rates for grade 1, 2, and 3 tumours were 90.12%, 64.4%, and 77.2% respectively (p = 0.019) with relapse rates of 70%, 55.6%, and 75.6% respectively (p = 0.04). Our current study is an attempt to validate these initial findings by expanding our data set to include data from the London Health Sciences Centre. A literature review on TNBC and grade was conducted, followed by a retrospective chart review for 305 TNBC patients from the Windsor Regional Hospital and 515 TNBC patients from the London Health Sciences Centre. The parameters for data collection included patient demographics, tumour demographics, therapies, and patient outcomes. We calculated all patient stages using both American Joint Committee on Cancer 7th edition (AJCC7) and the updated AJCC8 staging systems. Initial review of the data supports our earlier findings with a relapse rate of 12.5% in patients with grade 3 tumours and 17% in patients with grade 1 and grade 2 tumours. The completed data set will be analyzed and presented at the conference. Validating our previous findings of significantly inferior patient outcomes for grade 2 compared to grade 3 patients may alter the staging system used for TNBC patients. Citation Format: Mah-noor Malik, Neya Ramanan, Sarang Upneja, Muriel Brackstone, Lisa Porter, Bre-Anne Fifield, Caroline Hamm. Clinical Significance of Grade in Triple Negative Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-03-09.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".