Real-world practice patterns and attitudes towards de-escalation of bone-modifying agents in patients with bone metastases from breast and prostate cancer: A physician survey
Bibliographic record
Abstract
BACKGROUND: There remain questions around the optimal use of bone-modifying agents (BMAs) in patients with bone metastases from breast and castration-resistant prostate cancer (CRPC). A physician survey was performed to identify current practices, as well as perceptions around long-term BMA use, BMA de-escalation, and further BMA de-escalation after 2 years of use. METHODS: Canadian oncologists treating breast cancer or CRPC were surveyed via an anonymized online survey. The survey collected physician demographics, current practice patterns, perception on risk of symptomatic skeletal events (SSE) and BMA-associated toxicities, and attitudes towards further de-escalation of BMAs after 2 years of treatment. RESULTS: A total of 334 physicians in Canada were contacted, of which 295 were eligible on initial screening, and 65 completed the survey (response rate 22%): 35 treated breast cancer, 25 treated prostate cancer and 5 treated both. The most common BMA regimens in patients with no limitation in drug coverage were denosumab q4wks for 3-4 months followed by a de-escalation to q12wks (breast cancer) and denosumab q4wks (prostate cancer). In patients with provincial health coverage only the common choices were zoledronate q4wks for 3-4 months followed by de-escalation to q12wks (breast cancer) and denosumab q4wks (prostate cancer). There was equipoise regarding the benefit of continuing BMA beyond 2 years and interest in further trials of de-escalation of BMA in both breast and prostate cancer. The most favored alternative primary study endpoints to SSE were BMA toxicity (67.2%), pain (46.9%), and physical function (48.4%). CONCLUSION: Despite their extensive use and costs, questions around optimal use of BMAs still exist. Practice varies according to patient insurance coverage. However, most physicians are de-escalating BMAs. There is interest amongst clinicians in performing trials of de-escalation, especially after 2 years of 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".