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Record W1546725983 · doi:10.1038/bonekey.2015.85

Androgen-deprivation therapy and bone loss in prostate cancer patients: a clinical review

2015· review· en· W1546725983 on OpenAlexaff
Marc Bienz, Fred Saad

Bibliographic record

VenueBoneKEy Reports · 2015
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsMontreal General HospitalUniversité de Montréal
Fundersnot available
KeywordsMedicineAndrogen deprivation therapyDenosumabProstate cancerZoledronic acidOncologyOsteoporosisInternal medicineLife expectancyQuality of life (healthcare)Selective estrogen receptor modulatorCancerBreast cancerEstrogen receptor

Abstract

fetched live from OpenAlex

Androgen-deprivation therapy (ADT) has become a standard of care in the management of advanced prostate cancer or as an adjunct therapy. However, ADT is associated with a well-known deleterious effect on bone health, resulting in a decrease in bone-mass density (BMD) and increased risk for fracture. With the longer life expectancy of prostate cancer patients, improvement of the quality of life has become increasingly important. Therefore, adequate screening, prevention and treatment of BMD loss is paramount. Zoledronic acid and denosumab have shown promising results in recent studies, which has led to the Food and Drug Administration approval of these treatment options in various settings throughout the course of the disease, including the prevention of ADT-associated bone loss. This review focuses on the various parameters that impact BMD loss in men initiating ADT, on the specific effect of ADT on bone health and on various lifestyle modifications and treatment options such as bisphosphonates, osteoclast-targeted therapy and selective estrogen-receptor modulators that have shown promising results in recent studies.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.124
GPT teacher head0.449
Teacher spread0.325 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations53
Published2015
Admission routes1
Has abstractyes

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