Validation of EP1 Antibody Clone for Estrogen Receptor Immunohistochemistry in Breast Cancer
Bibliographic record
Abstract
Estrogen receptor (ER) tumor's status is critical for breast cancer management. A new rabbit antibody clone, EP1, is now available for ER status determination. The objective was to validate the EP1 antibody clone for its use in breast cancer ER status determination in a clinical setting against the previous standard, SP1. EP1 clone was assessed in 130 consecutive cases, including 50 ER-negative (<1% ER expression), 13 ER-low-positive (1% to 9% ER expression), and 67 ER-positive (≥10% ER expression). Using EP1 versus SP1, positive agreement (sensibility) was 92.5% and negative agreement (specificity) was 100%, leading to an overall agreement of 95.4%. All discordant cases (n=6) were ER-low-positive. SP1 was remeasured in 13 ER-low-positive and in 11 ER-negative cases. Overall agreement between SP1 initial tumor status and reassessment was 70.8% in those negative and low-positive cases. In conclusion, EP1 antibody has been validated for use in breast cancer with a positive agreement ≥90% and a negative agreement ≥95%, as recommended. Also, overall agreement between EP1 and SP1 was as good as between the SP1 initial status and SP1 reassessment.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".