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Record W2047390123 · doi:10.1002/pds.1068

Trends and determinants of antiresorptive drug use for osteoporosis among elderly women

2005· article· en· W2047390123 on OpenAlexaffabout
Sylvie Perreault, Alice Dragomir, Alain Desgagné, Lucie Blais, Michel Rossignol, Julie Blouin, Yola Moride, Louis‐Georges Ste‐Marie, Julio Fernandes

Bibliographic record

VenuePharmacoepidemiology and Drug Safety · 2005
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMontreal Police ServiceUniversité de Montréal
Fundersnot available
KeywordsMedicineOsteoporosisMedical prescriptionCohortPharmacoepidemiologyBone mineralInternal medicineCohort studyHormone replacement therapy (female-to-male)Proportional hazards modelHazard ratioConfidence intervalPharmacology

Abstract

fetched live from OpenAlex

AIM: It has been established that women who have had a first osteoporotic fracture are at a significantly greater risk of future fractures. Effective antiresorptive treatments (ART) are available to reduce this risk, yet little information is available on trends in ART drug use among the elderly. The objective is to estimate the rate ratio (RR) of having an ART prescription filled among elderly women and its relation to selected determinants from 1995 through 2001. METHOD: A cohort design was used. Through random sampling, we selected 40% of the women aged 70 years and older listed in the Régie de l'assurance maladie du Québec (RAMQ) health database. The women were grouped into four cohorts (for 1995, 1996, 1998 and 2000). January 1 was established as the index date within each cohort (1995, 1996, 1998 and 2000). The dependent variable was the RR of having at least one prescription of ART drugs filled during the year following the index date among women with and without prior use. ART users were divided in two groups: bone-specific drugs (bisphosphonates, calcitonin, raloxifen) and HRT (hormone replacement therapy). The independent variable was whether or not (control) there had been an osteoporotic-related fracture. The RR was determined for having at least one prescription of bone-specific drugs or of HRT filled during the year following the index date using a Cox regression adjusted for age, chronic disease score (CDS) and prior bone mineral density (BMD) test. RESULTS: Crude rates of BMD testing (per 500 person-years) ranged from 20.4 (1995) to 41.1 (2000) in women who had had an osteoporotic-related fracture, and from 4.4 to 15.3 in controls. The crude rate of women (per 100 person-years) who had had an osteoporotic-related fracture and who took at least one bone-specific drug during follow-up ranged from 1.9 in 1995 to 31 in 2000 among those with prior osteoporotic-related fracture, and from 0.5 in 1995 to 11 in 2000 for controls; the corresponding figures for HRT ranged 6.7 in 1995 to 13 in 2000, and from 8.4 in 1995 to 11 in 2000 respectively. BMD test is the only major factor affecting the adjusted RR of having a prescription filled for bone-specific drugs (RR of 10.44; 6.91-15.79 in 1995 and RR of 3.68; 3.30-4.10 in 2000) or HRT (RR of 2.08; 1.64-2.64 in 1995 and RR of 1.44; 1.17-1.77 in 2000), particularly among women who had not had prior use. The fact of having a fracture status does significantly affect the RR of having at least one bone-specific drug prescription filled only among women without prior use (RR of 1.71; 1.26-2.33 in 1996 and RR of 1.77; 1.44-2.19 in 2000). The fact of being younger did not affect the RR of having at least one prescription of bone-specific drugs filled, but being younger increased the RR of filling a prescription of HRT. CONCLUSIONS: Significant change was seen over time in the number of BMD tests ordered and ART use. Effective osteoporosis interventions are not optimal in the treatment of elderly women in a Canadian health-care system who have had an osteoporotic fracture, given that approximately 25% of women who had had an osteoporotic-related fracture were users of ART.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.378
Teacher spread0.339 · 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 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

Citations21
Published2005
Admission routes2
Has abstractyes

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