Abstract P2-05-33: Refining the prognostic value of Ki67 biomarker by ataxia telangiectasia mutated (ATM) status in a retrospective study of early stage hormone receptor positive breast cancer
Bibliographic record
Abstract
Abstract Purpose: The current study was designed to investigate the combined influence of ataxia telangiectasia mutated (ATM) and Ki67 on clinical outcome in early stage hormone receptor positive breast cancer (ES-HPBC), particularly in patients with smaller tumors (< 4 cm) and fewer than four positive lymph nodes. Methods: Formalin-fixed paraffin-embedded specimens of resected primary breast tumors from 532 patients diagnosed with early stage breast cancer were used to construct a tissue microarray. Samples from 297 patients were suitable for final statistical analysis. We detected ATM and Ki67 proteins using immunohistochemistry and quantified their expression with digital image analysis. Data on expression levels were subsequently correlated with clinical outcome. Results: Remarkably, ATM expression was useful to stratify the low Ki67 group into subgroups with better or poorer prognosis. Specifically, in the low Ki67 subgroup defined as having smaller tumors and no positive nodes, patients with high ATM expression showed better outcome than those with low ATM, with estimated survival rates of 96% and 89% respectively at 15 years follow up (p = 0.04). Similarly, low-Ki67 patients with smaller tumors, 1-3 positive nodes and high ATM also had significantly better outcomes than their low ATM counterparts, with estimated survival rates of 88% and 46% respectively (p=0.03) at 15 years follow up. Multivariable analysis indicated that the combination of high ATM and low Ki67 is prognostic of improved survival, independent of tumor size, grade, and lymph node status (p = 0.02). Low Ki67/high ATM expression independently predicts favorable disease survival in a multivariate model in low Ki67 subgroup of ES-HPBC (Stage I-III)Variablesp valueHR (95%CI)Low Ki67/high ATM vs Low Ki67/low ATM0.020.36 (0.15-0.88)ize (T1/2 vs T3/4)0.010.16 (0.04-0.69)LN status (- vs +)0.140.49 (0.20-1.25)LVI (_- vs +)0.160.51 (0.20-1.31)Grade (1/2 vs 3)<0.00010.28 (0.11-0.67)Age (<65 vs >65)0.010.26 (0.10-0.74) Conclusions: These data suggest that the prognostic value of Ki67 can be improved by analyzing ATM expression in ES-HPBC. Citation Format: Feng X, Li H, Kornarga E, Dean M, Lees-Miller S, Riabowol K, Magliocco A, Morris D, Watson P, Enwere E, Bebb G, Paterson A. Refining the prognostic value of Ki67 biomarker by ataxia telangiectasia mutated (ATM) status in a retrospective study of early stage hormone receptor positive breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-05-33.
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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 | 0.000 | 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".