Intra- and Interlaboratory Reproducibility of the Sensitivity to Endocrine Therapy Assay for Stage II/III Breast Cancer
Bibliographic record
Abstract
BACKGROUND: The sensitivity to endocrine therapy assay (SET2,3) predicts treatment outcomes in Stage II-III breast cancer. SET2,3 measures transcription related to estrogen and progesterone receptors (SETER/PR index) and the molecular subtype (RNA4: ESR1, PGR, ERBB2, AURKA) from formalin-fixed paraffin-embedded (FFPE) tissue sections. METHODS: We designed a nested study across 3 pathology laboratories, each testing 60 breast cancers twice in controlled batches. Laboratories macrodissected and directly homogenized the unstained FFPE tumor sections, then performed the QuantiGene Plex bead-based hybridization assay. SET2,3 was calculated centrally using predefined statistical R-scripts and applying pre-defined cutpoints. Concordance correlation coefficient (CCC) was calculated from continuous measurements and Kappa statistic from categorical results. A mixed-effects model estimated contributions to bias (fixed effects) and variance (random effects) from the replicated design. RESULTS: Intralaboratory (CCC 0.96-0.99) and interlaboratory (CCC 0.98-0.99) SET2,3 results were concordant, with rates of agreement for high/low categorization within (Kappa 0.83-0.93) and between laboratories (Kappa 0.87-0.88). The relative contributions to overall variance of SET2,3 measurements were 96.90% from biological differences between cancers, 0.67% from interlaboratory variability, and 2.44% from residual causes including intralaboratory replicates. Similar results were obtained with SETER/PR, the baseline prognostic index calculated using pathological or clinical tumor and nodal staging information, and the 4 individual genes (ESR1, PGR, ERBB2, and AURKA). CONCLUSION: Intra- and interpathology laboratory measurements of SET2,3 and its components were highly reproducible when tested from FFPE tumor sections.
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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 | 0.001 | 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) | 0.000 | 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".