Impact of Recurrence Score on Type and Duration of Chemotherapy in Breast Cancer
Bibliographic record
Abstract
Background: The use of Oncotype dx (Genomic Health, Redwood City, CA, U.S.A.) testing has been shown to change treatment decisions in approximately 30% of breast cancer (bca) cases, but research on how Recurrence Score testing has affected the type of chemotherapy offered is limited. We sought to determine if the availability of Oncotype dx testing resulted in a change to the type and duration of chemotherapy regimens used in the treatment of early-stage hormone receptor–positive bca. Methods: In a population-based cohort study, patients treated in the 2 years before the availability of Oncotype dx testing were compared with patients treated in the 2 years after testing availability. Charts were audited and divided into 2 groups: pre-Oncotype dx and post-Oncotype dx. The groups were compared for differences in duration of chemotherapy (12 weeks vs. >12 weeks), types of agents used (anthracycline vs. non-anthracycline), and myelosuppressive potential of the chosen regimen. Results: Of 834 patients who fulfilled the enrolment criteria, 360 fell into the pre-Oncotype dx era, and 474, into the post-Oncotype dx era. An increase of 11.2 percentage points, to 69.5% from 58.3%, was observed in the proportion of patients receiving short-course compared with long-course chemotherapy (p = 0.068). The proportion of patients prescribed anthracycline-containing regimens declined in the post-Oncotype dx era (47.7% pre vs. 32.2% post, p = 0.016). The selection of more-myelosuppressive chemotherapy protocols increased in the post-Oncotype dx era (67.4% pre vs. 78.8% post, p = 0.044). Conclusions: In the present study, the availability of Oncotype dx testing was observed to influence the choice of chemotherapy type in the setting of early-stage bca.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".