MétaCan
Menu
Back to cohort

Efficacy of Bisphosphonates in the Management of Skeletal Complications of Bone Metastases and Selection of Clinical Endpoints

2002· review· en· W2320853964 on OpenAlexaff
Pierre Major, Richard J. Cook

Bibliographic record

VenueAmerican Journal of Clinical Oncology · 2002
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsHamilton Regional Laboratory Medicine Program
Fundersnot available
KeywordsMedicineZoledronic acidClinical trialBisphosphonateBreast cancerProstate cancerMultiple myelomaBone metastasisOncologyClinical endpointInternal medicineCancerSurgeryOsteoporosis

Abstract

fetched live from OpenAlex

Bisphosphonates are the current standard of palliative care for patients with bone lesions from breast cancer and multiple myeloma. This article discusses the selection of endpoints and statistical methods used to assess clinical efficacy of bisphosphonate therapies in patients with bone metastases. Recent studies of pamidronate and zoledronic acid have set the standards for the design and conduct of multicenter, randomized, placebo-controlled trials to assess the clinical benefit of bisphosphonates in patients with bone metastases. Studies of zoledronic acid have demonstrated objective, significant, and enduring benefits in patients with a broad range of primary cancers, including prostate cancer, using robust clinical endpoints. Other bisphosphonates, including clodronate, have been investigated for the treatment of bone metastases, but these studies have been relatively small. This review first considers issues of trial design and analysis, with particular emphasis on the statistical requirements for the rigorous analysis of multiple events occurring in the same patient, and then reviews the results of bisphosphonate trials in patients with breast or prostate cancers metastatic to bone in the light of these statistical considerations.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.192
GPT teacher head0.539
Teacher spread0.348 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations94
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Clinical OncologySame topicBone health and treatmentsFrench-language works237,207