The association of clinical-pathologic factors and Oncotype Dx recurrence score (RS) in the outcome of early stage breast cancer.
Bibliographic record
Abstract
55 Background: Oncotype Dx recurrence score (RS) is routinely used to guide systemic therapy based on the estimated risk for distant relapse. Patients with early stage disease are also at risk for locoregional recurrence, and in some instances local relapse is the only site of failure. The objective of this study is to evaluate patient outcomes in association with known clinical-pathologic risk factors and RS. Observations in context of known clinical-pathologic features and RS may have important clinical implications relative to adjuvant locoregional therapy. Methods: This is an IRB approved retrospective study that includes patients with unilateral breast cancer and in whom the RS was reported. A total of 716 patients met this defined criteria. Seventy two percent underwent breast conserving therapy (BCS) and 28% underwent mastectomy; 68% had stage I and the remaining had > Stage II disease.The clinical-pathologic variables including age, stage, BRCA mutation, extent of surgery, and RS were studied in evaluating patient outcomes. Results: The median age was 56 years (27 to 84 years). The overall distribution of RS reported as low (18), intermediate (19-30), and high ( > 31) was 59%, 31%, and 10%, respectively. This distribution ratio was no different among patients treated with BCS and mastectomy. However, among BRCA mutation carriers there was a higher incidence of the high RS.Overall, the median follow up was over 3 years, and 25% of the patients have been followed over 5 years. The 3-year and 5-year any relapse-free survival was 93% and 89%, respectively. Age was significantly associated with observed inferior any relapse-free survival; 85% and 91% in women < 40 years vs > 40 years, respectively (p = 0.018). On univariate analysis, RS had no significant association with local regional relapse free survival. Further, associations between the clinical-pathologic features and RS using multivariate analysis will be presented. Conclusions: Observations with early follow up do not suggest a select role of RS in guiding risk tailored local regional therapy. Longer follow will further our understanding of patients at risk for local regional relapse.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".