Impacts of Prior Anti-Osteoporosis Treatments on Sequential Denosumab Responses in BMD Changes Among Postmenopausal Osteoporosis Women in East China: Real-World Data Analysis
Bibliographic record
Abstract
Guoyu Guan,1 Yanping Du,2,* Wenjing Tang,2 Minmin Chen,2 Weijia Yu,2 Huilin Li,2 Qun Cheng2,* 1Department of Geriatrics, Huadong Hospital, Fudan University, Shanghai, People’s Republic of China; 2Department of Osteoporosis and Bone Disease, Huadong Hospital, Fudan University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qun Cheng, Department of Osteoporosis and Bone Disease, Huadong Hospital, Fudan University, No. 221, Yan’an West Road, Shanghai, 200040, People’s Republic of China, Email chengqun@fudan.edu.cn Yanping Du, Department of Osteoporosis and Bone Disease, Huadong Hospital, Fudan University, No. 221, Yan’an West Road, Shanghai, 200040, People’s Republic of China, Email yanpingdu@fudan.edu.cnPurpose: This study aimed to investigate the impacts of prior anti-osteoporosis treatments on bone mineral density (BMD) changes in Chinese postmenopausal women with osteoporosis following 1-year Denosumab (Dmab) therapy.Patients and Methods: This retrospective cohort study enrolled 381 postmenopausal women, all receiving a 1-year Dmab treatment. Participants were stratified into five groups based on prior anti-osteoporosis treatments: no treatment (NT), alendronate (ALN), zoledronic acid (ZOL), teriparatide (TPT), and raloxifene (RAL). Potential factors influencing BMD changes were screened using least absolute shrinkage and selection operator (LASSO). The selected variables were then incorporated into a multivariate regression model to identify independent risk factors. Finally, after adjusting for confounders, the impacts of prior anti-osteoporosis treatment on sequential Dmab responses were evaluated.Results: 1) Further BMD increases were observed after sequential 1-year Dmab with prior use of other anti-osteoporosis drugs; 2) Compared to the NT group, ZOL significantly reduced BMD changes at the lumbar spine (LS), femoral neck (FN), and total hip (TH) (LS: β = − 0.01, P = 0.016; FN: β = − 0.01, P = 0.010; TH: β = − 0.01, P = 0.011); Significant negative associations with FN BMD changes were observed for the ALN group (β = − 0.01, P< 0.001), and the RAL group (β = − 0.01, P = 0.010) compared to the NT group; TPT showed no significant differences with the NT group at all sites; 3) Multiple analysis revealed baseline BMD were independently associated with changes in BMD (LS: β = − 0.04, P = 0.009; FN: β = − 0.19, P < 0.001; TH: β = − 0.14, P < 0.001).Conclusion: These findings indicated that prior anti-osteoporosis treatments differentially influenced BMD responses to 1-year Dmab therapy. While patients who had previously been treated with ZOL had limited subsequent BMD improvement, patients who had previously used TPT and had lower baseline BMD benefited more.Keywords: denosumab, alendronate, zoledronic acid, teriparatide, raloxifene, sequential treatment, bone mineral density, postmenopausal osteoporosis
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".