Feasibility outcomes of a randomised, multicentre, pilot trial comparing standard 6-monthly dosing of adjuvant zoledronate with a single one-time dose in patients with early stage breast cancer
Bibliographic record
Abstract
BACKGROUND: Adjuvant zoledronate is widely used in patients with early stage breast cancer (EBC), but its optimal duration and dosing interval is still unknown. While a single-dose of zoledronate can improve bone density for many years, a proper evaluation of its effects on breast cancer-related outcomes would require a large trial. In this pilot study we evaluated the feasibility of performing such a trial. METHODS: Eligible patients with EBC were randomised to receive either one dose of zoledronate or 7 doses (6-monthly dosing for 3 years). Feasibility was assessed by a combination of primary outcomes including: activation of at least 6 Ontario sites within a year, active participation (i.e. approaching eligible patients for study participation) of at least half of the medical oncologists, and enrolment of at least 100 patients across all sites within 9 months of the sixth site being activated. RESULTS: All 6 sites were activated within 1 year and of 47 medical oncologists, 27 (57%) approached patients. Between November 2018 and April 2020, 211 eligible patients were randomised, 106 (50.2%) to a single dose of zoledronate and 105 (49.8%) to 6-monthly dosing. Baseline characteristics of randomised patients included; median age 59 (range 36-88), ER and/or PR positive (85%), Her2 positive (23%), menopausal status (premenopausal [19%], perimenopausal [6.7%] and postmenopausal [74%]) and 74% received neo/adjuvant chemotherapy. CONCLUSIONS: All study feasibility endpoints were met in this trial comparing alternative schedules for adjuvant zoledronate. We will now seek funding for performing a larger efficacy trial.Trial registration: NCT03664687.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".