Effects of zoledronic acid on survival in patients with lung cancer and high baseline N-telopeptide (NTX) levels: Stratified by baseline bone alkaline phosphatase (BALP)
Bibliographic record
Abstract
7228 Background: Recently, it was shown that patients (pts) with bone metastases from lung cancer who had high NTX or BALP levels on study had a higher risk for skeletal-related events (SREs) and death compared with pts with low NTX or BALP. Zoledronic acid has been shown to prevent SREs; however, it is unknown whether there is a secondary survival benefit in this pt population. To assess the potential effect of zoledronic acid on survival in pts with bone metastases from lung cancer and high baseline NTX, we conducted a retrospective analysis of pts in a large, randomized, controlled trial. Methods: Patients with lung cancer and bone metastases were randomized to receive either 4 mg zoledronic acid or placebo for a total of 21 months. Survival data were evaluated in pts who had a high baseline NTX level (≥ 64 nmol/mmol) and baseline BALP level (retrospectively stratified by baseline BALP level according to these criteria: normal BALP < 146 U/L and high BALP ≥ 146 U/L). The relative risk (RR) of death was calculated for each pt group and for pts with high NTX levels overall compared with placebo. Results: The pts with high NTX levels (n = 144; men, 65% women, 35%) had a median age of 64 years. Among these pts, the RR of death was significantly reduced by 35% in pts who received zoledronic acid compared with placebo (RR = 0.650; P = .0244). The RR of death on study for pts who had both high baseline NTX and BALP levels (n = 97) was also significantly reduced by 46% in pts who received zoledronic acid compared with placebo (RR = 0.537; P = .0059). Among pts who had high baseline NTX and normal BALP levels (n = 47), the RR of death was similar between treatment groups (RR = 1.012; P = .9736). Conclusions: High levels of bone resorption may correlate with an increased risk of SREs and death. Zoledronic acid reduces bone turnover and the risk of SREs and may delay the progression of bone lesions. This retrospective analysis suggests that treatment with zoledronic acid may improve survival compared with placebo in pts with lung cancer who have high levels of bone metabolism, warranting further study in either other database analyses or prospective trials. [Table: see text]
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".