Clinical Utility of Multigene Profiling Assays in Early-Stage Breast Cancer
Bibliographic record
Abstract
BACKGROUND: This clinical practice guideline was developed to determine the level of evidence supporting the clinical utility of commercially available multigene profiling assays and to provide guidance about whether certain breast cancer patient populations in Ontario would benefit from alternative tests in addition to Oncotype dx (Genomic Health, Redwood City, CA, U.S.A.). METHODS: A systematic electronic Ovid search of the medline and embase databases sought out systematic reviews and primary literature. A systematic review and practice guideline was written by a working group and was then reviewed and approved by Cancer Care Ontario's Molecular Oncology Advisory Committee. RESULTS: Twenty-four studies assessing the clinical utility of Oncotype dx, Prosigna (NanoString Technologies, Seattle, WA, U.S.A.), EndoPredict (Myriad Genetics, Salt Lake City, U.S.A.), and MammaPrint (Agendia, Irvine, CA, U.S.A.) were included in the evidence base. CONCLUSIONS: The clinical utility of multigene profiling assays is currently established for an appropriate subset of patients with estrogen receptor-positive, her2-negative, node-negative breast cancer for whom a decision to give chemotherapy is difficult to make. For patients with estrogen receptor-positive tumours who receive tamoxifen alone, Oncotype dx, Prosigna, and EndoPredict validly identify a low-risk population with favourable outcomes, indicating that a low-risk assay result is actionable and the decision to withhold chemotherapy is supported. Clinical evidence indicates that a high Oncotype dx recurrence score can predict for chemotherapy benefit, but a high Prosigna or EndoPredict score, although prognostic, is not, based on clinical trial evidence, directly actionable. Prosigna and EndoPredict are statistically more likely to identify a population at risk for recurrence beyond 5 years, but that information is currently not actionable because of a lack of interventional studies.
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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 | 0.050 | 0.140 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".