Expectations of breast-conserving therapy: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Early-stage breast cancer is often treated with breast-conserving therapy (BCT), including lumpectomy with radiation therapy. Patients' expectations of BCT remain largely unknown. Expectations affect perceptions of treatment-related experiences and health-related quality of life (HR-QOL) outcomes. Our primary aim was to describe expectations of BCT among patients with early breast cancer through qualitative methods. Our secondary aim was to inform preoperative patient education and improve the patient experience through knowledge. METHODS: We used a grounded-theory approach to investigate a convenience sample of 22 women with stage I and II breast cancer who were treated with BCT at a single hospital in New York City between May and August 2016. Semi-structured interviews were conducted in person and by telephone. Open-ended questions covered participants' expectations of treatment experiences and outcomes. Data was analyzed in a line-by-line approach to identify emergent themes related to patient expectations. Interviews continued until no new themes emerged. RESULTS: Analysis of data identified the following themes related to patient expectations of BCT: experience of cancer care, recovery, appearance, and HR-QOL. Despite preoperative informed consent and teaching, participants expressed few expectations preoperatively, owing to a lack of knowledge about the process of care. Lack of expectations preoperatively was compensated with available care and resources postoperatively. CONCLUSIONS: Patients in our sample had a surprisingly limited understanding of what to expect during treatment with BCT. Despite available information and preoperative teaching, patients have a clear knowledge gap regarding BCT. These findings suggest patients often undergo cancer treatment with trust rather than complete understanding of the process. This data may be used to enhance preoperative discussions aimed at preparing patients for surgery and treatment.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".