Informative tools to optimize neoadjuvant therapy in ER positive, HER2 negative breast cancers.
Bibliographic record
Abstract
e12595 Background: Neoadjuvant therapy (NAT) in HR+/HER2- tumors is often disputable. While the role of Oncotype DX has been well established in adjuvant settings, its clinical utility and potential implementation for prediction of NAT benefit requires further study. This ongoing study aims to report the feasibility of Oncotype DX testing on core biopsy specimens prior to NAT in patients with operable HR+/HER2- breast cancer. The effect of the recurrence score (RS) on systemic treatment recommendations and its correlation to dynamic markers of proliferation and NAT response will be evaluated. Methods: Participants with clinical T2-T4 and/or node positive HR+/HER2- breast cancer had Oncotype DX testing done prior to NAT. Clinico-pathological information, treatment regimens, clinical, radiologic, and pathological responses were recorded. Results: Of the 48 patients with HR+/HER2- breast cancer referred to BC Cancer Vancouver for consideration of NAT between September 2021 and January 2023, 26 were eligible and enrolled in the study. The success rate of the Oncotype DX on core biopsy samples was 96%. The mean turnaround time from patient consent to RS report was 19 calendar days. Approximately 32% of tumors had a RS equal or higher than 26 while 4% had a score less than 10. Nearly 25% of neoadjuvant treatment recommendations were changed based on the RS. Overall, 33% of patients received neoadjuvant chemotherapy, 54% received neoadjuvant endocrine treatment, and 12.5% proceeded with upfront surgery. Conclusions: The success rate of Oncotype DX testing on core biopsy samples was excellent. There were multiple factors that influenced trial enrollment, highlighting the low uptake and equipoise of NAT use in HR+/HER2- tumors. The Oncotype DX testing resulted in a change in systemic treatment plan in 25% of patients. Analyses are ongoing to correlate the recurrence score to NAT response, dynamic Ki-67 changes and breast MRI changes. Clinical trial information: NCT03790813 .
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".