Changes in estrogen receptor (ER), progesterone receptor (PR) and HER2/neu status with time: Discordance rates between primary and metastatic breast pathology samples
Bibliographic record
Abstract
1024 Background: The occurrence of changes in tumor receptor profile (ER, PR and HER-2/neu) between primary and metastatic tissue has been recognised and may have significant treatment implications. Previous reports on receptor discordance rates have tended to be from sub-studies of clinical trials. We sought to evaluate the degree of ER, PR and HER-2/neu receptor discordance in patients treated at two Canadian cancer centres. Methods: Archival data was collected on patients for whom tissue from both primary and metastatic sites was available. Patients with recurrences in the breast or axilla were excluded. ER, PR and HER-2/neu status in the primary and metastasis were compared. Additional information including adjuvant therapy and time to metastasis biopsy was gathered. Results: To date, data is available on 80 patients. Hormone receptor (HR) status was available for 96% of primaries and 56% of metastases. HR status on both the primary and the metastasis was performed in 51% of cases. The discordance rate for ER was 21% (2-sided p=0.0096). 12% of patients changed from ER+ to ER- and 9% changed from ER- to ER+. The discordance rate for PR was 37% (2-sided p=0.0001), with all of these patients changing from PR+ to PR-. No significant HR discordance was found among different adjuvant hormone therapy subgroups. There was no correlation between HR discordance and time to rebiopsy. No discordance for HER-2/neu was found. Conclusions: Significant discordance for HR status was observed, 21% for ER and 37% for PR. HER-2/neu discordance was not observed. We are currently exploring the practical implications of these discordance rates on the management of advanced breast cancer patients in a prospective trial. No significant financial relationships to disclose.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".