Adjuvant hormonal therapy (AHT) in women with early stage breast cancer (BC).
Bibliographic record
Abstract
11053 Background: The ASCO technology assessment on adjuvant use of AI states that optimal AHT for a postmenopausal woman with HR-positive BC should now include an AI. We assessed uptake and patterns of AHT use in early stage HR-positive BC at a regional cancer center. Methods: A retrospective review of patients diagnosed with HR-positive early stage BC from January 2004 to December 2005 treated at our center was performed. Data included patient demographics, dates of diagnosis, treatment, last follow-up, AHT choices considered, patient compliance, and treatment toxicity. Patient risks for disease recurrence and mortality were estimated using adjuvantonline. Factors predicting a preference for AI use were identified using univariable and multivariable analysis. Results: 900 patients were identified for the stated period of time with HR-positive early stage BC. 340 patients have been evaluated. Median age was 59 years. Menopausal status was post-/ pre- in 267/73 patients. Stage was I/IIA/IIB in 202/95/43 patients. 267 patients were lymph node (LN) negative. ER, PR and Her2/neu status were positive/negative/unknown in 332/7/1, 292/46/2 and 11/69/260 patients. Initial AHT choice was tamoxifen/anastrozole/letrozole/exemastane/none in 196/79/9/2/54 patients. Of those started upfront on tamoxifen, plan to switch to an AI was stated in 41%. Statistically significant factors associated with any adjuvant AI use included disease stage, menopausal status as well as individual physician preferences. In further analysis, patients’ compliance and toxicity will be reported. Correlation of recurrence risk, as determined through adjuvantonline, with upfront selection of an AI has also been performed. Conclusion: Guidelines have stated the use of an AI (upfront, sequential or extended) should be considered in HR-positive early stage BC. Results from this study provide further insights on the uptake of such therapy as well as factors (disease related, patient and physician preferences) influencing adjuvant treatment decision-making. A prospective trial assessing treatment decision regarding AHT is also in progress. (This study is sponsored by the Canadian Breast Cancer Foundation) No significant financial relationships to disclose.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".