Clinical Utility of Genomic Assay in Node-Positive Early-Stage Breast Cancer
Bibliographic record
Abstract
Breast cancer (BC) is the most common malignancy among women in Canada. Adjuvant treatment in early BC can reduce the risk of BC recurrence. Historically, the decision for adjuvant chemotherapy for early BC was made only based on clinical and tumour characteristics. In recent years, there has been an effort toward developing genomic assays as a predictive and prognostic tool to improve precision in estimating disease recurrence, sensitivity to systemic treatment and ultimately with clinical utility for guidance regarding adjuvant systemic treatment(s). There are various commercial genomic tests available for early-stage ER+/HER-2 negative BC. This paper will review the Oncotype DX 21-gene Recurrence Score (RS), MammaPrint, EndoPredict, Prosigna®, and Breast Cancer Index (BCI) genomic assays. We will also focus on these genomic assays’ clinical application and utility in node-positive early-stage BC based on the most recent evidence and guidance recommendations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".