Estrogen/progesterone receptor and HER2 discordance between primary tumor and brain metastases in breast cancer and its effect on treatment and survival
Bibliographic record
Abstract
BACKGROUND: Breast cancer treatment is based on estrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth factor receptor 2 (HER2). At the time of metastasis, receptor status can be discordant from that at initial diagnosis. The purpose of this study was to determine the incidence of discordance and its effect on survival and subsequent treatment in patients with breast cancer brain metastases (BCBM). METHODS: A retrospective database of 316 patients who underwent craniotomy for BCBM between 2006 and 2017 was created. Discordance was considered present if the ER, PR, or HER2 status differed between the primary tumor and the BCBM. RESULTS: The overall receptor discordance rate was 132/316 (42%), and the subtype discordance rate was 100/316 (32%). Hormone receptors (HR, either ER or PR) were gained in 40/160 (25%) patients with HR-negative primary tumors. HER2 was gained in 22/173 (13%) patients with HER2-negative primary tumors. Subsequent treatment was not adjusted for most patients who gained receptors-nonetheless, median survival (MS) improved but did not reach statistical significance (HR, 17-28 mo, P = 0.12; HER2, 15-19 mo, P = 0.39). MS for patients who lost receptors was worse (HR, 27-18 mo, P = 0.02; HER2, 30-18 mo, P = 0.08). CONCLUSIONS: Receptor discordance between primary tumor and BCBM is common, adversely affects survival if receptors are lost, and represents a missed opportunity for use of effective treatments if receptors are gained. Receptor analysis of BCBM is indicated when clinically appropriate. Treatment should be adjusted accordingly. KEY POINTS: 1. Receptor discordance alters subtype in 32% of BCBM patients.2. The frequency of receptor gain for HR and HER2 was 25% and 13%, respectively.3. If receptors are lost, survival suffers. If receptors are gained, consider targeted treatment.
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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 | 0.000 | 0.000 |
| 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".