Effect of serum HER2, TIMP-1, and CAIX on outcome in HER2+ metastatic breast cancer patients treated in first line with lapatinib or trastuzumab combined with taxane: NCIC CTG MA.31.
Bibliographic record
Abstract
617 Background: The lapatinib-taxane combination led to shorter PFS than trastuzumab-taxane in HER2+ metastatic breast cancer. We investigated the prognostic and predictive effects of pretreatment serum HER2, CA IX, and TIMP-1. Methods: MA.31 accrued 652 patients; 537 (82%) were centrally-confirmed HER2+. Biomarkers were categorized for univariate and multivariate predictive investigations with a median cut-point, ULN cut-points (15 ng/ml for HER2; 506 pg/ml for CAIX; 454 pg/ml for TIMP-1), and custom cut-points (30 and 100 ng/ml for HER2). Stratified step-wise forward Cox multivariate analysis used continuous and categorical biomarkers for PFS in the ITT and central HER2+ populations; central HER2+ biomarker results are shown. Results: Serum was banked for 472 (72%) of 652 patients. Higher serum HER2 (>median; >15; >30; or >100 ng/ml; p=0.05-0.002); higher CAIX (>median; >506 pg/ml; p=0.02; p=0.001); and higher TIMP-1 (>median; >454 pg/ml; p=0.001; p=0.02) had worse univariate PFS. In multivariate analysis, higher continuous TIMP-1 was associated with significantly worse PFS: HR=1.001 (95% CI=1.000-1.002; p=0.004). Continuous serum HER2 and CAIX were not significantly associated with PFS. HER2 of 15 ng/ml or higher had shorter PFS (p=0.02); higher categorical CAIX had worse PFS (p=0.01-0.08). The interaction terms of HER2, CAIX, and TIMP-1 with treatment were not significant. Multivariate PFS categorical serum results (Table). Conclusions: Higher levels of serum TIMP-1, CAIX, and HER2 were significant prognostic biomarkers of shorter PFS. No serum biomarker was predictive of differential response to lapatinib vs. trastuzumab. Evaluation of TIMP-1 and CAIX targeted therapy in addition to HER2 targeted therapy is warranted in patients with elevated serum levels of these biomarkers. p-value HR Lower CI Higher CI LTax vs TTax 0.001 1.58 1.20 2.06 Adjuvant anthracyclines 0.011 1.58 1.11 2.25 Adjuvant other therapy 0.043 3.88 1.04 14.41 EGFR (% stain) 0.012 1.01 1.001 1.01 Serum HER2 (>15 vs <15 ng/ml) 0.023 1.51 1.06 2.15 Serum CAIX (>506 vs <506 pg/ml) 0.005 1.54 1.14 2.08 *DH and JH contributed equally.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".