Reflex MammaPrint testing on breast core biopsies: A single center experience.
Bibliographic record
Abstract
e12581 Background: Breast cancer genomic assays are well established in the adjuvant setting, but still evolving in the neoadjuvant setting. Recent data shows that MammaPrint (MP)/BluePrint (BP) genomic assays in the neoadjuvant setting can reclassify hormone receptor positive (HR+), HER2 negative (HER2-) tumors into intrinsic phenotypes with corresponding responses to neoadjuvant therapy (NAC). We performed reflex MP/BP assays on invasive breast cancer core biopsies and evaluated the relationships between clinical risk, molecular risk and intrinsic phenotype. Methods: 150 consecutive HR+, HER2- invasive breast cancers were identified by core biopsy in a tertiary care cancer center and underwent reflex MP/BP testing by an external central laboratory between July 2021 and Jan 2022. Retrospective review was completed on patient demographics and tumor characteristics; descriptive statistics were performed. Results: Of 150 newly diagnosed HR+ HER2- breast cancers, 141 successfully had a reflex MP/BP test performed; 9 were not performed due to technical feasibility or clerical error. Of the 141 patients with a completed MP/BP assay, 7 had recurrent disease, and 8 had metastatic disease, these were excluded. Patients were categorized as clinically high (cHR) or low risk (cLR) using the criteria from the MINDACT trial and as molecularly high risk (MP HR) or low risk (MP LR) per their MP results. We then grouped patients with discordant clinical and molecular risk. We then examined clinical features and NAC receipt amongst these clinical and molecular risk groups. Conclusions: There was discordance between clinical and molecular risk in 38% of our cohort, 20% were cLR/MP and 18% were cHR/MP LR. The decision to give NAC was primarily driven by clinical risk as only 1 patient with cLR/MP HR received NAC. Amongst cHR/MP LR 87% did not get NAC, but this appears to have been a clinical decision as only 7 of these patients had a pre-operative oncology visit at which MP/BP was mentioned. Most (72%) of > cN1 patients received NAC, of the 5 who didn’t, 4 were in the MP LR group and had a pre-operative oncology visit where MP was mentioned. In this select group the genomic assay may have influenced the decision to withhold NAC. Reflex genomic assays for HR+ HER2- breast cancer may not be useful; the decision to integrate molecular risk into the decision for NAC is multifactorial and stage of disease may be most impactful. Further work is needed in this area. [Table: see text] [Table: see text]
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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, 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".