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Record W3134532066 · doi:10.3390/jcm10051140

Duration of Bisphosphonate Drug Holidays in Osteoporosis Patients: A Narrative Review of the Evidence and Considerations for Decision-Making

2021· review· en· W3134532066 on OpenAlexaff
Kaleen N. Hayes, Elizabeth M. Winter, Suzanne M. Cadarette, Andrea M. Burden

Bibliographic record

VenueJournal of Clinical Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMedicineDiscontinuationBisphosphonateDrug holidayOsteonecrosis of the jawOsteoporosisSurrogate endpointNarrative reviewDrugInternal medicineSurgeryIntensive care medicinePharmacologyFamily medicine

Abstract

fetched live from OpenAlex

Bisphosphonates are first-line therapy for osteoporosis, with alendronate, risedronate, and zoledronate as the main treatments used globally. After one year of therapy, bisphosphonates are retained in bone for extended periods with extended anti-fracture effects after discontinuation. Due to this continued fracture protection and the potential for rare adverse events associated with long-term use (atypical femoral fractures and osteonecrosis of the jaw), a drug holiday of two to three years is recommended for most patients after long-term bisphosphonate therapy. The recommendation for a drug holiday up to three years is derived primarily from extensions of pivotal trials with alendronate and zoledronate and select surrogate marker studies. However, certain factors may modify the duration of bisphosphonate effects on a drug holiday and warrant consideration when determining an appropriate time off-therapy. In this narrative review, we recall what is currently known about drug holidays and discuss what we believe to be the primary considerations and areas for future research regarding drug holiday duration: total bisphosphonate exposure, type of bisphosphonate used, bone mineral density and falls risk, and patient sex and body weight.

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)0.110
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.908
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.110
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
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 head0.171
GPT teacher head0.527
Teacher spread0.356 · 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 designSystematic review
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

Citations40
Published2021
Admission routes1
Has abstractyes

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