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Denosumab for prevention of fractures in men receiving androgen deprivation therapy (ADT) for prostate cancer (PC)

2009· article· en· W3080944707 on OpenAlexaff
Fred Saad, Matthew Ryan Smith, Blair Egerdie, Teuvo L.J. Tammela, Rachel Feldman, Jiří Heráček, Maciej Szwedowski, Chunlei Ke, B.Z. Leder, Carsten Goessl

Bibliographic record

VenueJournal of Clinical Oncology · 2009
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsDenosumabMedicineAndrogen deprivation therapyProstate cancerClinical endpointOsteoporosisBone mineralSurgeryInternal medicineIncidence (geometry)UrologyRandomized controlled trialCancer

Abstract

fetched live from OpenAlex

5056 Background: ADT increases bone resorption, reduces bone mineral density (BMD), and increases fracture risk. Previously, we reported that denosumab, a fully human monoclonal antibody against RANKL, increased BMD and reduced the incidence of vertebral fractures in men with PC on ADT. We now describe in further detail the effects of denosumab on fractures at other skeletal sites. Methods: Men receiving ADT for nonmetastatic PC were randomized to receive subcutaneous denosumab 60 mg every 6 months (n = 734) or placebo (n = 734), with daily calcium and vitamin D supplements for 3 years. Men < 70 years old were required to have low BMD or a history of osteoporotic fracture. The primary endpoint was percentage change in lumbar spine BMD at 24 months. Key secondary endpoints were subject incidence of new vertebral fractures and fractures at any site (excluding fractures from severe trauma or pathologic fractures) over 3 years. Here, we evaluate the frequency of all fractures and fractures at key osteoporotic sites. The planned sample size (N = 1226) provided power to differentiate effects of denosumab from placebo for the primary and key secondary endpoints. Results: As previously reported, denosumab reduced the incidence of new vertebral fractures by 62% (p = 0.006), fractures at any site by 28% (p = 0.10), and multiple fractures at any site by 72% (p = 0.006) over 3 years. In a post-hoc analysis, we found a consistent trend showing a positive effect of denosumab on nonvertebral fractures. The occurrence of any fractures (counting all fractures within a subject) over 3 years was lower with denosumab than placebo (43 vs 77, p < 0.01). The subject incidence of fractures at 6 high-risk sites (wrist, humerus, hip, pelvis, leg [excluding patella], and clavicle) was numerically lower with denosumab (15 vs 24 placebo; p = 0.12). Also, fewer subjects in the denosumab arm than in the placebo arm reported fractures at key osteoporotic sites (e.g., 2 for denosumab vs 10 for placebo at the radius). Overall rates of adverse events were balanced between treatment arms. Conclusions: Denosumab significantly reduced the incidence of new vertebral fractures and in a post-hoc analysis, showed a trend toward a positive effect on nonvertebral fractures in men receiving ADT for nonmetastatic PC. [Table: see text]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.139
GPT teacher head0.543
Teacher spread0.403 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2009
Admission routes1
Has abstractyes

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