Cardiovascular Safety in Postmenopausal Women and Men With Osteoporosis Treated With Denosumab and Zoledronic Acid: A Post‐Authorization Safety Study
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Bibliographic record
Abstract
Abstract Osteoporosis and cardiovascular disease are common in older adults. Treatment of osteoporosis reduces the burden of debilitating fractures; however, it is important to understand the benefit versus risk of treatment. This study evaluates the risk of stroke (ischemic or hemorrhagic) and myocardial infarction (MI) among postmenopausal women and men initiating osteoporosis treatment with denosumab (receptor activator of nuclear factor κB ligand [RANKL] inhibitor) or zoledronic acid (bisphosphonate) between October 2010 and June 2019. A retrospective cohort study employing the new user/active comparator design was conducted. Analyses were conducted separately in two national US commercial databases, MarketScan® and Optum® for reproducibility. Inverse probability of treatment and censoring weighting was employed to control for confounding and informative censoring. Cumulative risks at 6‐month, 12‐month, and 36‐month time points were calculated and adjusted risk ratios and differences (with 95% confidence intervals [CIs]) were estimated. In MarketScan® and Optum® databases, 96,611 and 73,127 patients met all study eligibility criteria, respectively. At 36 months, the risk ratio estimates (zoledronic acid referent group) were 1.22 (95% CI, 0.77–1.66) and 0.97 (95% CI, 0.63–1.32) for MI and 1.00 (95% CI, 0.61–1.40) and 0.87 (95% CI, 0.56–1.17) for stroke in MarketScan and Optum, respectively. Most of the treatment associations across the other time periods and outcomes also had 95% CIs including the null value. In these large samples of real‐world US patients, no increased risk in MI and stroke were identified for up to 36 months of treatment in denosumab users compared with zoledronic acid users. © 2023 Amgen. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it