Cost-Effectiveness Analysis of 12-Versus 4-Weekly Administration of Bone-Targeted Agents in Patients with Bone Metastases from Breast and Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
A cost–utility analysis was performed based on the Rethinking Clinical Trials (REaCT) bone-targeted agents (BTA) clinical trial that compared 12-weekly (once every 12 weeks) (n = 130) versus 4-weekly (once every 4 weeks) (n = 133) BTA dosing for metastatic breast and castration-resistant prostate (CRPC) cancer. Using a decision tree model, we calculated treatment and symptomatic skeletal event (SSE) costs as well as quality-adjusted life-years (QALYs) for each treatment option. Deterministic and probabilistic sensitivity analyses were performed to assess the robustness of the study findings. The total cost of BTA treatment in Canadian dollars (C$) and estimated QALYs was C$8965.03 and 0.605 QALY in the 4-weekly group versus C$5669.95 and 0.612 QALY in the 12-weekly group, respectively. De-escalation from 4-weekly to 12-weekly BTA reduces cost (C$3293.75) and improves QALYs by 0.008 unit, suggesting that 12-weekly BTA dominates 4-weekly BTA in breast and CRPC patients with bone metastases. Sensitivity analysis suggests high levels of uncertainty in the cost-effectiveness findings. De-escalation of bone-targeted agents is cost-effective from the Canadian public payer’s perspective.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".