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Too Much, Too Little, Too Late to Start Again? Assessing the Efficacy of Bisphosphonates in Patients with Bone Metastases from Breast Cancer

2006· review· en· W2156070031 on OpenAlexaff
Mark Clemons, George Dranitsaris, David E.C. Cole, M. Corona Gainford

Bibliographic record

VenueThe Oncologist · 2006
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreCancer Care Ontario
Fundersnot available
KeywordsMedicineBreast cancerNatural historyBone metastasisOncologyCancerInternal medicine

Abstract

fetched live from OpenAlex

The diagnosis of bone metastases can be a devastating occurrence for any woman with breast cancer. In this setting, bone metastases can result in skeletal-related events (SREs) such as pathologic fracture, spinal cord compression, and hypercalcemia. Several trials have confirmed the ability of bisphosphonates to reduce or delay these skeletal complications, and they should now be considered standard care for these women. The analysis of SREs is the typical primary end point in bisphosphonate studies. While not undermining their importance, the definition of SREs does not include complications important to patients, such as pain and immobility. It is these symptoms that are most frequently reported by patients, and bone pain and quality of life (QoL) are often measured as secondary end points in these trials. Bone pain and QoL measures are not standardized and are difficult to compare among patient populations. We do not yet know the true efficacy of bisphosphonates as analgesics or how they impact QoL. This paper reviews the current efficacy measures used in recent bisphosphonate trials and discusses their benefits and limitations. It also explores the role of bone biomarkers and their potential use in monitoring treatment response.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.044
GPT teacher head0.377
Teacher spread0.333 · 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 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

Citations32
Published2006
Admission routes1
Has abstractyes

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