Adjuvant bisphosphonate use in patients with early stage breast cancer: Patient perspectives on treatment acceptability and potential de-escalation
Bibliographic record
Abstract
BACKGROUND: Despite the increasing use of adjuvant bisphosphonates for early stage breast cancer (EBC), little is known about the patient experience with such treatments. A patient survey was performed to identify current prescribing practices, perceptions around the role of treatment, the impact of treatment on patients' quality of life, and future trial designs. METHODS: EBC patients who had either completed or were currently receiving adjuvant bisphosphonates were sent an anonymized survey. The survey collected information on patient and disease characteristics, bisphosphonate scheduling, compliance, and tolerance. Questions also assessed patient interest in trials of de-escalated bisphosphonate therapy. RESULTS: A total of 255 patients were contacted, with 164 eligible respondents (eligible response rate 164/255, 64.3%). Median patient age was 52 years (range 28 to 82 years). The majority (111/163, 68.1%) were postmenopausal at the time of diagnosis, 23.3% (38/163) were premenopausal, and 7.4% (12/163) were perimenopausal. Most patients (78%) had received chemotherapy. Zoledronate was the most commonly used bisphosphonate (92%), with the majority receiving treatment every 6 months for 3 years (73%). While 66% (107/161) of respondents had experienced side effects with treatment, most had, or expected to, complete treatment (154/163, 94%). Provided there was no detriment in breast cancer outcomes, there was strong interest in future studies of de-escalating adjuvant bisphosphonate therapy. CONCLUSION: While most patients tolerate their treatment, there is interest in performing trials of de-escalation of these agents.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".