MétaCan
Menu
← Back to cohort
Record W2898560392 · doi:10.1093/annonc/mdy284.054

Phase III double-blind study evaluating lens opacifications (LO) in patients with nonmetastatic prostate cancer (PCa) receiving denosumab (Dmab) for bone loss due to androgen deprivation therapy (ADT)

2018· article· en· W2898560392 on OpenAlexfundno aff
Scott T. Tagawa, Tian Dai, Danielle Jandial

Bibliographic record

VenueAnnals of Oncology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsnot available
FundersDOD Prostate Cancer Research ProgramWeill Cornell Medical CollegeCilagAstellas PharmaNational Cancer InstituteGenomic HealthMemorial Sloan-Kettering Cancer CenterProstate Cancer FoundationEli Lilly and CompanyU.S. Department of DefenseSanofiAbbott LaboratoriesNational Institutes of HealthLondon Health Sciences CentreAmgen
KeywordsMedicineAndrogen deprivation therapyProstate cancerClinical endpointDenosumabUrologyRandomized controlled trialPlaceboInternal medicineSurgeryOsteoporosisCancerPathology

Abstract

fetched live from OpenAlex

Background: Men with PCa undergoing ADT experience bone loss that may be associated with fracture risk and reduced survival. Therapy with Dmab (Prolia®, Amgen, Inc) significantly increased bone mass and reduced vertebral fracture risk in men with nonmetastatic PCa receiving ADT. However, in that study (unlike other Dmab randomized trials), cataracts were reported more often in the Dmab group (4.7% vs 1.2% for placebo [PBO]). This trial (NCT00925600) assessed the effect of Dmab on LO (cataract) development or progression in men with nonmetastatic PCa receiving ADT.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.435
Teacher spread0.311 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of Oncology→Same topicConnexins and lens biology→French-language works237,207→