Abstract P1-07-13: Prognostic relevance of statistically standardized estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) in tamoxifen(TAM)-treated NCIC CTG MA.14 patients
Bibliographic record
Abstract
Abstract Background: Poor inter-laboratory comparability of common clinically used breast cancer biomarkers led to a proposal of statistical standardization (SS) of laboratory results, similar to bone mineral density (BMD) z-scores. This analysis is the first utilization of SS in a trial where all women received TAM. Methods: MA.14 allocated 667 postmenopausal women to TAM +/− Octreotide LAR (OCT) based on locally determined ER/PR, without HER2 status. At 9.8 yrs median follow-up, the secondary endpoint of relapse-free survival (RFS) had a non-significant hazard ratio (HR) for TAM-OCT to TAM of 0.87 (95% CI 0.63–1.21; p = 0.40). 299 patients who were representative of MA.14 patients by treatment and stratification factors (exact Fisher p-values=0.19–0.90) had their tumors centrally assessed for ER, PR, and HER2 by RT-PCR. Continuous values were used for SS of each biomarker. Univariate (uni) assessment used similar categorizations as those for BMD, assigning ER/PR/HER2 values by number of standard deviations (SD) about the mean (Group 1, z-score ≥1.0 SD below mean; Group 2, z-score <1.0 SD below mean; Group 3, z-score ≤1.0 SD above mean; Group 4, z-score >1.0 SD above mean). A log-rank statistic was used to test for differences between SS biomarker groups with K-M plots for graphical description. Multivariate (multi) effects of SS biomarkers and baseline patient characteristics on RFS were examined with exploratory (un)stratified Cox step-wise forward regression, adding a factor if likelihood ratio criterion was p ≤ 0.05. Sensitivity analyses used a prior external HER2+ cut-point of ≥1.32 SD. Results: 292 patient samples passing internal analytical quality control were included in this analysis. Uni analyses indicated SS ER was not associated with RFS (p = 0.31). SS PR had a significant uni effect on RFS [p = 0.03; Group 4 compared to Group 1, HR of 0.33 (95% CI 0.12–0.90); Group 3 compared to Group 1, HR of 0.42 (95% CI 0.21–0.83); and Group 2 compared to Group 1 HR of 0.70 (95%CI 0.36–1.37)]. SS HER2 also had a significant uni effect on RFS [p = 0.004; Group 4 compared to Group 1, HR of 0.90 (95% CI 0.37–2.16)]; Group 3 compared to Group 1, HR of 0.39 (95% CI 0.18–0.84); and, Group 2 compared to Group 1, HR of 0.34 (95% CI 0.16–0.70)]. Multi stratified/unstratified Cox models indicated T1 tumours (p = 0.02/p = 0.0002) and higher SS PR (p = 0.02/0.01) were associated with significantly longer RFS; other unstratified results showed that N-ve patients had better RFS (p < .0001), while local ER/PR status did not impact RFS (p > 0.05). The HER2+ cut-point of ≥1.32 SD indicated directionally worse RFS (uni p-value=0.05; multi p-value=0.06). Discussion: In MA.14, all women received TAM. Local ER/PR status using categorical or semi-quantitative values did not impact RFS. A statistically standardized approach using continuous centralized ER, PR, HER2 by RT-PCR demonstrated that increasing PR values were associated with better RFS. Evaluation in other trials may provide support for this methodology. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P1-07-13.
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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 | 0.000 | 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) | 0.003 | 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".