Decision Support for a Woman Considering Continuing Extended Endocrine Therapy for Breast Cancer: A Case Study
Bibliographic record
Abstract
This case study evaluated decision coaching with a breast cancer survivor considering continuing extended endocrine therapy from eight years to 10 years. The survivor, aged 58 years and who completed surgery and chemotherapy eight years ago, was concerned about side effects of endocrine therapy. Decision coaching based on the Ottawa Decision Support Framework involved an oncology nurse using the Ottawa Personal Decision Guide. Compared to baseline (2 out of 4), decisional comfort improved (3 out of 4) post decision coaching. The survivor felt more certain, but wanted further advice from her oncologist. She was leaning toward discontinuing endocrine therapy given she valued quality of life over a small risk of recurrence. Audio-recording analysis using the Decision Support Analysis Tool revealed high decision coaching quality (10/10). Breast cancer survivors facing preference-sensitive decisions about extended endocrine therapy could be supported with decision coaching by oncology nurses to ensure informed values-based decisions.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".