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Record W1515768733 · doi:10.4137/cmt.s1958

Metastatic Bone Disease in Patients with Solid Tumors–-Burden of Bone Disease and the Role of Zoledronic Acid

2009· article· en· W1515768733 on OpenAlexaff
Vera Hirsh

Bibliographic record

VenueClinical Medicine Therapeutics · 2009
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineZoledronic acidBisphosphonateBreast cancerMultiple myelomaSpinal cord compressionBone diseaseCancerMalignancyBone painOncologyInternal medicineBone metastasisDiseaseSurgeryOsteoporosisSpinal cord

Abstract

fetched live from OpenAlex

Bisphosphonates have become an integral component of the therapeutic repertoire for cancer patients at risk for skeletal-related events (SREs) such as pathologic fractures, bone pain requiring palliative radiotherapy, the need for orthopedic surgery, spinal cord compression, and hypercalcemia of malignancy because of bone metastases. Administered via monthly 15-minute infusion of up to 4 mg (depending on creatinine clearance rate), zoledronic acid (ZOL) has been approved for preventing SREs in patients with bone metastases from any solid tumor or bone lesions from multiple myeloma. Although there have been limited head-to-head comparison trials between bisphosphonates, ZOL displayed benefits beyond pamidronate in a large-scale comparative trial in patients with bone metastases from breast cancer. Monitoring of serum creatinine levels and oral health is important to ensure safety and comfort during treatment. In addition to the established benefits of bisphosphonates in the advanced cancer setting, there is a strong preclinical rationale and emerging clinical evidence that ZOL has antitumor activities and can delay metastasis in patients with early breast cancer. Studies are underway in patients with other tumor types, and the role of bisphosphonates is likely to evolve.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.364
Teacher spread0.334 · 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 designObservational
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

Citations1
Published2009
Admission routes1
Has abstractyes

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