Mammostrat As an Immunohistochemical Multigene Assay for Prediction of Early Relapse Risk in the Tamoxifen Versus Exemestane Adjuvant Multicenter Trial Pathology Study
Bibliographic record
Abstract
PURPOSE: Some postmenopausal patients with hormone-sensitive early breast cancer remain at high risk of relapse despite endocrine therapy and, in addition, might benefit from adjuvant chemotherapy. The challenge is to prospectively identify such patients. The Mammostrat test uses five immunohistochemical markers to stratify patients regarding recurrence risk and may inform treatment decisions. We tested the efficacy of this panel in the Tamoxifen versus Exemestane Adjuvant Multicenter (TEAM) trial. PATIENTS AND METHODS: Pathology blocks from 4,598 TEAM patients were collected, and tissue microarrays (TMAs) were constructed. The cohort was 47% node-positive, and 36% of patients in the cohort were treated with adjuvant chemotherapy. Triplicate 0.6-mm(2) TMA cores were stained, and positivity for p53, HTF9C, CEACAM5, NDRG1, and SLC7A5 was assessed. Cases were assigned a Mammostrat risk score, and distant relapse-free survival (DRFS) and disease-free survival (DFS) were analyzed. RESULTS: In multivariate regression analyses, which were corrected for conventional clinicopathologic markers, Mammostrat provided significant additional information on DRFS after endocrine therapy in estrogen receptor (ER) -positive node-negative patients (n = 1,226) who did not receive chemotherapy (P = .004). Additional analyses in all patients not exposed to chemotherapy, irrespective of nodal status (n = 2,559) and in the entire cohort (n = 3,837) showed Mammostrat scores provided additional information on DRFS in these groups (P = .001 and P < .001, respectively; multivariate analyses). No differences were seen between the two endocrine treatment regimens. CONCLUSION: The Mammostrat score predicts DRFS for patients treated with exemestane and patients treated with tamoxifen followed by exemestane irrespective of nodal status and chemotherapy. The ability of this test to provide additional outcome data after treatment provides additional evidence of its use in risk stratification of ER-positive postmenopausal patients with breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".