Assessment and management of bone health in women with oestrogen receptor‐positive breast cancer receiving endocrine therapy: position statement summary
Bibliographic record
Abstract
INTRODUCTION: Representatives appointed by relevant Australian medical societies used a systematic approach for adaptation of guidelines (ADAPTE) to formulate clinical consensus recommendations on assessment and management of bone health in women with oestrogen receptor-positive early breast cancer receiving endocrine therapy. The current evidence suggests that women receiving adjuvant aromatase inhibitors and pre-menopausal woman treated with tamoxifen have accelerated bone loss and that women receiving adjuvant aromatase inhibitors have increased fracture risk. Both bisphosphonates and denosumab prevent bone loss; additionally, denosumab has proven anti-fracture benefit in post-menopausal women receiving aromatase inhibitors for hormone receptor-positive breast cancer. MAIN RECOMMENDATIONS: Women considering endocrine therapy need fracture risk assessment, including clinical risk factors, biochemistry and bone mineral density measurement, with monitoring based on risk factors. Weight-bearing exercise and vitamin D and calcium sufficiency are recommended routinely. Anti-resorptive treatment is indicated in women with prevalent or incident clinical or morphometric fragility fractures, and should be considered in women with a T score (or Z score in women aged < 50 years) of < - 2.0 at any site, or if annual bone loss is ≥ 5%, considering baseline bone mineral density and other fracture risk factors. Duration of anti-resorptive treatment can be individualised based on absolute fracture risk. Relative to their skeletal benefits, risks of adverse events with anti-resorptive treatments are low. CHANGES IN MANAGEMENT AS RESULT OF THE POSITION STATEMENT: Skeletal health should be considered in the decision-making process regarding choice and duration of endocrine therapy. Before and during endocrine therapy, skeletal health should be assessed regularly, optimised by non-pharmacological intervention and, where indicated, anti-resorptive treatment, in an individualised, multidisciplinary approach.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".