Possible survival benefits from zoledronic acid treatment in patients with bone metastases from solid tumours and poor prognostic features—An exploratory analysis of placebo-controlled trials
Bibliographic record
Abstract
BACKGROUND: Zoledronic acid (ZOL) is an important component of therapy for patients with metastatic bone disease (MBD) to reduce the risk of skeletal-related events (SREs). We evaluated overall survival (OS) in patients with MBD secondary to solid tumours included in placebocontrolled ZOL trials. PATIENTS AND METHODS: Exploratory analyses were performed using databases from three randomised trials of ZOL versus placebo. 1126 patients (ZOL, n=731; placebo, n=395) with complete baseline data for 18 predefined parameters were evaluated for OS. Relative risks (RRs) with 95% confidence intervals were assessed using stratified and adjusted Cox regression models. Baseline covariates defining patient populations with significantly different effects of ZOL treatment on OS (identified by stepwise backward elimination) were included in multivariate models. RESULTS: Although OS was similar between the overall treatment groups, ZOL significantly improved OS in the subset of patients (n=423; 38%) with elevated baseline NTX (≥100 nmol/mmol creatinine; RR, 0.692; P=.0028). Notably, this effect was independent of SRE prevention. Additional covariates associated with OS benefits with ZOL (e.g., low albumin, SRE history, elevated lactate dehydrogenase, shorter cancer duration) were characteristic of advanced disease. CONCLUSION: These exploratory analyses suggest a beneficial effect of ZOL on OS in patients with highly aggressive or advanced MBD.
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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 | 0.033 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.012 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".