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Record W2124466636 · doi:10.1185/030079907x188198

Prescriptions for vitamin Damong patients taking antiresorptive agents in Canada

2007· article· en· W2124466636 on OpenAlexaffabout
David A. Hanley, Qiaoyi Zhang, Marie‐Claude Meilleur, Panagiotis Mavros, Shuvayu S. Sen

Bibliographic record

VenueCurrent Medical Research and Opinion · 2007
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsMerck Canada Inc. (Canada)University of Calgary
Fundersnot available
KeywordsMedicineVitamin D and neurologyMedical prescriptionRaloxifeneAlfacalcidolCalcitriol receptorErgocalciferolInternal medicineDenosumabOsteoporosisCholecalciferolPharmacologyBreast cancerBone mineralCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Data on the rate of concomitant vitamin D use with antiresorptive medications are limited. Such information is important because vitamin D is indicated in patients with osteoporosis, including those receiving bisphosphonates, and there is evidence of inadequate use by these patients. OBJECTIVE: To examine prescription vitamin D utilization patterns. RESEARCH DESIGN AND METHODS: A retrospective analysis of patients aged > or = 65 years was conducted in a Canadian pharmacy-insurance organization (RAMQ) who received at least one prescription for an antiresorptive agent (i.e., alendronate, risedronate, raloxifene) from January 1, 1996, through December 31, 2003, and did not switch to any other agent during the 1-year post period. Data on prescriptions of vitamin D formulations on the RAMQ formulary (e.g., alfacalcidol, calcitriol, cholecalciferol, doxercalciferol, ergocalciferol) were also captured. No data on generic or over-the-counter vitamin D preparations were available. A vitamin D and antiresorptive agent possession ratio (R(P)) was computed as: R(P) = SigmaD(SPVD) / SigmaD(SARR) where SigmaD(SPVD) = the sum of the days of supply with prescription vitamin D and SigmaD(SARR) = the sum of days of supply with alendronate, risedronate, or raloxifene A vitamin D and antiresorptive agent overlap ratio (R(0)) was computed as: R(0) = SigmaD(SPVDOARR) / SigmaD(SARR) where SigmaD(SPVDOARR) = the sum of days of supply of prescription vitamin D overlapping with alendronate, risedronate, or raloxifene, and SigmaD(SARR) = the sum of the days of supply with alendronate, risedronate, or raloxifene. RESULTS: A total of 46,226 antiresorptive treatment users were identified, > 90% of whom were women. A total of 17,151 (37.1%) had concomitant vitamin D prescriptions. The average duration of prescription therapy with alendronate, risedronate, or raloxifene was 247 days; and the mean duration of prescription vitamin D therapy was 83 days. Patients had a supply of vitamin D for 55% of days of antiresorptive agents therapy (R(P) = 0.55) and a vitamin D supply overlapping with 24% of their days on antiresorptive agents (R(o) = 0.24). Possession and overlap ratios were significantly higher in patients receiving once-weekly bisphosphonate prescriptions compared with once-daily regimens (bisphosphonates or raloxifene). Vitamin D prescriptions were also significantly more likely in patients receiving prescriptions for once-weekly bisphosphonates (odds ratio (OR) = 4.65; 95% CI = 4.29-5.05; p < 0.0001) and once-daily bisphosphonates (OR = 1.91; 95% CI = 1.76-2.07; p < 0.0001) compared with once-daily raloxifene. CONCLUSIONS: Despite the benefits of vitamin D for osteoporosis, most patients ( approximately 63%) receiving prescriptions for antiresorptive agents were not taking vitamin D, indicating a substantial treatment gap. The study is limited by including data only on (1) pharmacy claims, which do not equate to patient behaviors, such as filling or refilling prescriptions and/or taking the medications; and (2) prescription (but not generic or over-the-counter) vitamin D formulations.

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)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.164
GPT teacher head0.465
Teacher spread0.300 · 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 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

Citations8
Published2007
Admission routes2
Has abstractyes

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